|Centenarian hotspots in Denmark||Via bioRxiv: Centenarian Hotspots in Denmark. The abstract: Background: The study of regions with high prevalence of centenarians is motivated by a desire to find determinants of healthy ageing. While existing research has focused on selected candidate geographical regions, we...|
|Response to To Increase Trust, Change the Social Design Behind Aggregated Biodiversity Data|
Nico Franz and Beckett W. Sterner recently published a preprint entitled "To Increase Trust, Change the Social Design Behind Aggregated Biodiversity Data" on bioRxiv http://dx.doi.org/10.1101/157214 Below is the abstract:
Growing concerns about the quality of aggregated biodiversity data are lowering trust in large-scale data networks. Aggregators frequently respond to quality concerns by recommending that biologists work with original data providers to correct errors "at the source". We show that this strategy falls systematically short of a full diagnosis of the underlying causes of distrust. In particular, trust in an aggregator is not just a feature of the data signal quality provided by the aggregator, but also a consequence of the social design of the aggregation process and the resulting power balance between data contributors and aggregators. The latter have created an accountability gap by downplaying the authorship and significance of the taxonomic hierarchies â frequently called "backbones" â they generate, and which are in effect novel classification theories that operate at the core of data-structuring process. The Darwin Core standard for sharing occurrence records plays an underappreciated role in maintaining the accountability gap, because this standard lacks the syntactic structure needed to preserve the taxonomic coherence of data packages submitted for aggregation, leading to inferences that no individual source would support. Since high-quality data packages can mirror competing and conflicting classifications, i.e., unsettled systematic research, this plurality must be accommodated in the design of biodiversity data integration. Looking forward, a key directive is to develop new technical pathways and social incentives for experts to contribute directly to the validation of taxonomically coherent data packages as part of a greater, trustworthy aggregation process.
Below I respond to some specific points that annoyed me about this article, at the end I try and sketch out a more constructive response. Let me stress that although I am the current Chair of the GBIF Science Committee, the views expressed here are entirely my own.
Trust and social relations
Trust is a complex and context-sensitive concept...First, trust is a dependence relation between a person or organization and another person or organization. The first agent depends on the second one to do something important for it. An individual molecular phylogeneticist, for example, may rely on GenBank (Clark et al. 2016) to maintain an up-to-date collection of DNA sequences, because developing such a resource on her own would be cost prohibitive and redundant. Second, a relation of dependence is elevated to being one of trust when the first agent cannot control or validate the second agent's actions. This might be because the first agent lacks the knowledge or skills to perform the relevant task, or because it would be too costly to check.
Trust is indeed complex. I found this part of the article to be fascinating, but incomplete. The social network GBIF operates in is much larger than simply taxonomic experts and GBIF, there are relationships with data providers, other initiatives, a broad user community, government agencies that approve it's continued funding, and so on. Some of the decisions GBIF makes need to be seen in this broader context.
For example, the article challenges GBIF for responding to errors in the data by saying that these should be "corrected at source". This a political statement, given that data providers are anxious not to ceed complete control of their data to aggregators. Hence the model that GBIF users see errors, those errors get passed back to source (the mechanisms for tis is mostly non-existent), the source fixes it, then the aggregator re-harvests. This model makes assumptions about whether sources are either willing or able to fix these errors that I think are not really true. But the point is this is less about not taking responsibility, but instead avoiding treading on toes by taking too much responsibility. Personally I think should take responsibility for fixing a lot of these errors, because it is GBIF whose reputation suffers (as demonstrated by Franz and Sterner's article).
A third step is to refrain from defending backbones as the only pragmatic option for aggregators (Franz 2016). The default argument points to the vast scale of global aggregation while suggesting that only backbones can operate at that scale now. The argument appears valid on the surface, i.e., the scale is immense and resources are limited. Yet using scale as an obstacle it is only effective if experts were immediately (and unreasonably) demanding a fully functional, all data-encompassing alternative. If on the other hand experts are looking for token actions towards changing the social model, then an aggregator's pursuit of smaller-scale solutions is more important than succeeding with the 'moonshot'.
Scalability is everything. GBIF is heading towards a billion occurrence records and several million taxa (particularly as more and more taxa from DNA-barcoding taxa are added). I'm not saying that tractability trounces trust, but it is a major consideration. Anybody advocating a change has got to think about how these changes will work at scale.
I'm conscious that this argument could easily be used to swat away any suggestion ("nice idea, but won't scale") and hence be a reason to avoid change. I myself often wish GBIF would do things differently, and run into this problem. One way around it is to make use of the fact that GBIF has some really good APIs, so if you want GBIF to do something different you can build a proof of concept to show what could be done. If that is sufficiently compelling, then the case for trying to scale it up is going to be much easier to make.
As a social model, the notion of backbones (Bisby 2000) was misguided from the beginning. They disenfranchise systematists who are by necessity consensus-breakers, and distort the coherence of biodiversity data packages that reflect regionally endorsed taxonomic views. Henceforth, backbone-based designs should be regarded as an impediment to trustworthy aggregation, to be replaced as quickly and comprehensively as possible. We realize that just saying this will not make backbones disappear. However, accepting this conclusion counts as a step towards regaining accountability.
This strikes me as hyperbole. "They disenfranchise systematists who are by necessity consensus-breakers". Really? Having backbones in no way prevents people doing systematic research, challenging existing classifications, or developing new ones (which, if they are any good, will become the new consensus).
We suggest that aggregators must either author these classification theories in the same ways that experts author systematic monographs, or stop generating and imposing them onto incoming data sources. The former strategy is likely more viable in the short term, but the latter is the best long-term model for accrediting individual expert contributions. Instead of creating hierarchies they would rather not 'own' anyway, aggregators would merely provide services and incentives for ingesting, citing, and aligning expert-sourced taxonomies (Franz et al. 2016a).
Backbones are authored in the sense that they are the product of people and code. GBIF's is pretty transparent (code and some data on github, complete with a list of problems). Playing Devil's advocate, maybe the problem here is the notion of authorship. If you read a paper with 100's of authors, why does that give you any greater sense of accountabily? Is each author going to accept responsibility for (or being to talk cogently about) every aspect of that paper? If aggregators such as GBIF and Genbank didn't provide a single, simple way to taxonomically browse the data I'd expect it would be the first thing users would complain about. There are multiple communities GBIF must support, including users who care not at all about the details of classification and phylogeny.
Having said that, obviously these backbone classifications are often problematic and typically lag behind current phylogenetic research. And I accept that they can impose a certain view on how you can query data. GenBank for a long time did not recognise the Ecdysozoa (nematodes plus arthropods) despite the evidence for that group being almost entirely molecular. Some of my research has been inspired by the problem of customising a backbone classification to better more modern views (doi:10.1186/1471-2105-6-208).
If handling multiple classifications is an obstacle to people using or contributing data to GBIF, then that is clearly something that deserves attention. I'm a little sceptical, in that I think this is similar to the issue of being able to look at multiple versions of a document or GenBank sequence. Everyone says it's important to have, I suspect very few people ever use that functionality. But a way forward might be to construct a meaningful example (in other words an live demo, not a diagram with a few plant varieties).
We view this diagnosis as a call to action for both the systematics and the aggregator communities to reengage with each other. For instance, the leadership constellation and informatics research agenda of entities such as GBIF or Biodiversity Information Standards (TDWG 2017) should strongly coincide with the mission to promote early-stage systematist careers. That this is not the case now is unfortunate for aggregators, who are thereby losing credibility. It is also a failure of the systematics community to advocate effectively for its role in the biodiversity informatics domain. Shifting the power balance back to experts is therefore a shared interest.
Having vented, let me step back a little and try and extract what I think the key issue is here. Issues such as error correction, backbones, multiple classifications are important, but I guess the real issue here is the relationship between experts such as taxonomists and systematists, and large-scale aggregators (note that GBIF serves a community that is bigger than just these researchers). Franz and Sterner write:
...aggregators also systematically compromise established conventions of sharing and recognizing taxonomic work. Taxonomic experts play a critical role in licensing the formation of high-quality biodiversity data packages. Systems of accountability that undermine or downplay this role are bound to lower both expert participation and trust in the aggregation process.
I think this is perhaps the key point. Currently aggregation tends to aggregate data and not provenance. Pretty much every taxonomic name has at one point or other been published by somebody. For various reasons (including the crappy way most nomenclature databases cite the scientific literature) by the time these names are assembled into a classification by GBIF the names have virtually no connection to the primary literature, which also means that who contributed the research that led to that name being minted (and the research itself) is lost. Arguably GBIF is missing an opportunity to make taxonomic and phylogenetic research more visible and discoverable (I'd argue this is a better approach than Quixotic efforts to get all biologists to always cite the primary taxonomic literature).
Franz and Sterner's article is a well-argued and sophisticated assessment of a relationship that isn't working the way it could. But to talk in terms of "power balance" strikes me as miscasting the debate. Would it not be better to try and think about aligning goals (assuming that is possible). What do experts want to achieve? What do they need to achieve those goals? Is it things such as access to specimens, data, literature, sequences? Visibility for their research? Demonstrable impact? Credit? What are the impediments? What, if anything, can GBIF and other aggregators do to help? In what way can facilitating the work of experts help GBIF?
In my own "early-stage systematist career" I had a conversation with Mark Hafner about the Louisiana State University Museum providing tissue samples for molecular sequencing, essentially a "project in a box". Although Mark was complaining about the lack credit for this (a familiar theme) the thing which struck me was how wonderful it would be to have such a service - here's everything you need to do your work, go do some science. What if GBIF could do the same? Are you interested in this taxonomic group, well here's the complete sum of what we know so far. Specimens, literature, DNA sequences, taxonomic names, the works. Wouldn't that be useful?
Franz and Sterner call for "both the systematics and the aggregator communities to reengage with each other". I would echo this. I think that the sometimes dysfunctional relationship between experts and aggregators is partly due to the failure to build a community of researchers around GBIF and its activities. The focus of GBIF's relationship with the scientific community has been to have a committee of advisers, which is a rather traditional and limited approach ("you're a scientist, tell us what scientists want"). It might be better served if it provided a forum for researchers to interact with GBIF, data providers, and each other.
I stated this blog (iPhylo) years ago to vent my frustrations about TreeBASE. At the time I was fond of a quote from a philosopher of science that I was reading, to the effect that we only criticise those things that we care about. I take Franz and Sterner's article to indicate that they care about GBIF quite a bit ;). I'm looking forward to more critical discussion about how we can reconcile the needs of experts and aggregators as we seek to make global biodiversity data both open and useful.
|Copyright and the Use of Images as Biodiversity Data||Willi Egloff, Donat Agosti, Puneet Kishor, David Patterson, and Jeremy A. Miller have published an interesting preprint entitled âCopyright and the Use of Images as Biodiversity Dataâ|
DOI:10.1101/087015 in which they argue that taxonomic images aren't copyrightable. I'm not convinced, and have commented on the bioRxiv site. Frustratingly bioRxiv puts comments into a moderation queue (in my opinion the stupidest thing to do if you want to enable conversation) so I've posted my comment here.
It seems to me that there are two deeply problematic aspects to this claim. The first is that taxonomic illustration is not creative. This seems, at best, arguable. I've illustrated new species, and it sure felt like I was doing creative work. Arguably every creative work adheres to conventions of a discipline, how does this by itself make copyright irrelevant?
|bioRxiv is here|
For years many in the biological sciences community have been jealous of the exist of arXiv. This preprint server allows researchers to distribute their work widely to all comers. On occasion when when there have been debates about mimicking arXiv for biology there has been skepticism about the nature of the outcomes (my own rejoinder […]
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|Evolutionary dynamics of CRISPR gene drives|
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tHapMix: simulating tumour samples through haplotype mixtures
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|Toxicity Management in CAR T cell therapy for B-ALL: Mathematical modelling as a new avenue for improvement|
Toxicity Management in CAR T cell therapy for B-ALL: Mathematical modelling as a new avenue for improvement.
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|Worth a read: A simple proposal for the publication of journal citation distributions||This paper in BioRXiv is definitely worth checking out. Abstract is below: Although the Journal Impact Factor (JIF) is widely acknowledged to be a poor indicator of the quality of individual papers, it is used routinely to evaluate research and researchers. Here, we present a simple method for generating the citation distributions that underlie JIFs. … Continue reading Worth a read: A simple proposal for the publication of journal citation distributions |
|Should we try to infer trees on tree-unlikely matrices?|
Spermatophyte morphological matrices that combine extinct and extant taxa notoriously have low branch support, as traditionally established using non-parametric bootstrapping under parsimony as optimality criterion. Coiro, Chomicki & Doyle (2017) recently published a pre-print to show that this can be overcome to some degree by changing to Bayesian-inferred posterior probabilities. They also highlight the use of support consensus networks for investigating potential conflict in the data. This is a good start for a scientific community that so far has put more of their trust in either (i) direct visual comparison of fossils with extant taxa or (ii) collections of most parsimonious trees inferred based on matrices with high level of probably homoplasious characters and low compatibility. But do those matrices really require or support a tree? Here, I try to answer this question.
Coiro et al. mainly rely on a recent matrix by Rothwell & Stockey (2016), which marks the current endpoint of a long history of putting up and re-scoring morphology-based matrices (Coiro et al.âs fig. 1b). All of these matrices provide, to various degrees, ambiguous signal. This is not overly surprising, as these matrices include a relatively high number of fossil taxa with many data gaps (due to preservation and scoring problems), and combine taxa that perished a hundred or more millions years ago with highly derived, possibly distant-related modern counterparts.
Rothwell & Stockey state (p. 929) "As is characteristic for the results from the analysis of matrices with low character state/taxon ratios, results of the bootstrap analysis (1000 replicates) yielded a much less fully resolved tree (not figured)." Coiro et al.âs consensus trees and network based on 10,000 parsimony bootstrap replicates nicely depicts this issue, and may explain why Rothwell & Stockey decided against showing those results. When studying an earlier version of their matrix (Rothwell, Crepet & Stockey 2009), they did not provide any support values, citing a paper published in 2006, where the authors state (Rothwell & Nixon 2006, p. 739): ââ¦ support values, whether low or high for particular groups, would only mislead the reader into believing we are presenting a proposed phylogeny for the groups in question. Differences among most-parsimonious trees are sufficient to illuminate the points we wish to make here, and support values only provide what we consider to be a false sense of accuracy in these assessmentsâ.
Do the data support a tree?
The problem is not just low support. In fact, the tree showed by Rothwell & Stockey with its âpectinate arrangementâ conflicts in parts with the best-supported topology, a problem that also applied to its 2009 predecessor. This general âpectinateâ arrangement of a large, low or unsupported grade is not uncommon for strict consensus trees based on morphological matrices that include fossils and extant taxa (see e.g. the more proximal parts of the Tree of Life, e.g. birds and their dinosaur ancestors).
The support patterns indicate that some of the characters are compatible with the tree, but many others are not. Of the 34 internodes (branches) in the shown tree (their fig. 28 shows a strict consensus tree based on a collection of equally parsimonious trees), 12 have lower bootstrap support under parsimony than their competing alternatives (Fig. 1). Support may be generally low for any alternative, but the ones in the tree can be among the worst.
The main problem is that the matrix simply does not provide enough tree-like signal to infer a tree. Delta Values (Holland et al. 2002) can be used as a quick estimate for the treelikeliness of signal in a matrix. In the case of large all-spermatophyte matrices (Hilton & Bateman 2006; Friis et al. 2007; Rothwell, Crepet & Stockey 2009; Crepet & Stevenson 2010), the matrix Delta Values (mDV) are â¥ 0.3. For comparison, molecular matrices resulting in more or less resolved trees have mDV of â¤ 0.15. The individual Delta Values (iDV), which can be an indicator of how well a taxon behaves during tree inference, go down to 0.25 for extant angiosperms â very distinct from all other taxa in the all-spermatophyte matrices with low proportions of missing data/gaps â and reach values of 0.35 for fossil taxa with long-debated affinities.
The newest 2016 matrix is no exception with a mDV of 0.322 (the highest of all mentioned matrices), and iDVs range between 0.26 (monocots and other extant angiosperms) and 0.39 for Doylea mongolica (a fossil with very few scored characters). In the original tree, Doylea (represented by two taxa) is part of the large grade and indicated as the sister to Gnetidae (or Gnetales) + angiosperms (molecular trees associate the Gnetidae with conifers and Ginkgo). According to the bootstrap analysis, Doylea is closest to the extant Pinales, the modern conifers. Coiro et al. found the same using Bayesian inference. Their posterior probability (PP) of a Doylea-Podocarpus-Pinus clade is 0.54, and Rothwell & Stockeyâs Doylea-Ginkgo-angiosperm clade conflicts with a series of splits with PPs up to 0.95.
Do the data require a tree?
As David made a point in an earlier post, neighbour-nets are not really âphylogenetic networksâ in the evolutionary sense. Being unrooted and 2-dimensional, they donât depict a phylogeny, which has to be a sort of (rooted) tree, a one-dimensional graph with time as the only axis (this includes reticulation networks where nodes can be the crossing point of two internodes rather than their divergence point). The neighbour-net algorithm is an extension into two dimensions of the neighbour-joining algorithm, the latter infers a phylogenetic tree serving a distance criterion such as minimum evolution or least-squares (Felsenstein 2004). Essentially, the neighbour-net is a âmeta-phylogeneticâ graph inferring and depicting the best and second-best alternative for each relationship. Thus, neighbour-nets can help to establish whether the signal from a matrix, treelike or not as it is the cases here, supports potential and phylogenetic relationships, and explore the alternatives much more comprehensively than would be possible with a strict-consensus or other tree (Fig. 2).
In addition, neighbour-nets usually are better backgrounds to map patterns of conflicting or partly conflicting support seen in a bootstrap, jackknife or Bayesian-inferred tree sample. In Fig. 3, I have mapped the bootstrap support for alternative taxon bipartitions (branches in a tree) on the background of the neighbour-net in Fig. 2.
Obvious and less-obvious relationships are simultaneously revealed, and their competing support patterns depicted. Based on the graph, we can see (edge lengths of the neighbour-net) that there is a relatively weak primary but substantial bootstrap support for the Petriellales (a recently described taxon new to the matrix) as sister to the angiosperms. Several taxa, or groups of closely related taxa, are characterised by long terminal edges/edge bundles, rooting in the boxy central part of the graph. Any alternative relationship of these taxa/taxon groups receives equally low support, but there are notable differences in the actual values.
There is little signal to place most of the fossil âseed fernsâ (extinct seed plants) in relation to the modern groups, and a very ambiguous signal regarding the relationship of the Gnetidae (or Gnetales) with the two main groups of extant seed plants, the conifers (Pinidae; see C. Earleâs gymnosperm database) and angiosperms (for a list and trees, see P. Stevensâ Angiosperm Phylogeny Website).
The Gnetidae is a strongly distinct (also genetically) group of three surviving genera, being a persistent source of headaches for plant phylogeneticists. Placed as sister to the Pinaceae (âGnepineâ hypothesis) in early molecular trees (long-branch attraction artefact), the currently favoured hypothesis (âGnetiferâ) places the Gnetidae as sister to all conifers (Pinatidae) in an all-gymnosperm clade (including Gingko and possibly the cycads).
As favoured by the branch support analyses, and contrasting with the preferred 2016 tree, the two Doyleas are placed closest to the conifers, nested within a commonly found group including the modern and ancient conifers and their long-extinct relatives (Cordaitales), and possibly Ginkgo (Ginkgoidae). In the original parsimony strict consensus tree, they are placed in the distal part as sister to a Gnetidae and Petriellales + angiosperms (possibly long-branch attraction). The grade including the âprimitive seed fernsâ (Elkinsia through Callistophyton), seen also in Rothwell and Stockeyâs 2016 tree, may be poorly supported under maximum parsimony (the criterion used to generate the tree), but receives quite high support when using a probabilistic approach such as maximum likelihood bootstrapping or Bayesian inference to some degree (Fig. 3; Coiro, Chomicki & Doyle 2017).
Numerous morphological matrices provide non-treelike signals. A tree can be inferred, but its topology may be only one of many possible trees. In the framework of total evidence, this may be not such a big problem, because the molecular partitions will predefine a tree, and fossils will simply be placed in that tree based on their character suites. Without such data, any tree may be biased and a poor reflection of the differentiation patterns.
By not forcing the data in a series of dichotomies, neighbour-nets provide a quick, simple alternative. Unambiguous, well-supported branches in a tree will usually result in tree-like portions of the neighbour net. Boxy portions in the neighbour-net pinpoint the ambiguous or even problematic signals from the matrix. Based on the graph, one can extract the alternatives worth testing or exploring. Support for the alternatives can be established using traditional branch support measures. Since any morphological matrix will combine those characters that are in line with the phylogeny as well as those that are at odds with it (convergences, character misinterpretations), the focus cannot be to infer a tree, but to establish the alternative scenarios and the support for them in the data matrix.
Coiro M, Chomicki G, Doyle JA. 2017. Experimental signal dissection and method sensitivity analyses reaffirm the potential of fossils and morphology in the resolution of seed plant phylogeny. bioRxiv DOI:10.1101/134262
Crepet WL, Stevenson DM. 2010. The Bennettitales (Cycadeoidales): a preliminary perspective of this arguably enigmatic group. In: Gee CT, ed. Plants in Mesozoic Time: Morphological Innovations, Phylogeny, Ecosystems. Bloomington: Indiana University Press, pp. 215-244.
Denk T, Grimm GW. 2009. The biogeographic history of beech trees. Review of Palaeobotany and Palynology 158: 83-100.
Felsenstein J. 2004. Inferring Phylogenies. Sunderland, MA, U.S.A.: Sinauer Associates Inc.
Friis EM, Crane PR, Pedersen KR, Bengtson S, Donoghue PCJ, Grimm GW, Stampanoni M. 2007. Phase-contrast X-ray microtomography links Cretaceous seeds with Gnetales and Bennettitales. Nature 450: 549-552 [all important information needed for this post is in the supplement to the paper; a figure showing the actual full analysis results can be found at figshare]
Hilton J, Bateman RM. 2006. Pteridosperms are the backbone of seed-plant phylogeny. Journal of the Torrey Botanical Society 133: 119-168.
Holland BR, Huber KT, Dress A, Moulton V. 2002. Delta Plots: A tool for analyzing phylogenetic distance data. Molecular Biology and Evolution 19: 2051-2059.
Rothwell GW, Crepet WL, Stockey RA. 2009. Is the anthophyte hypothesis alive and well? New evidence from the reproductive structures of Bennettitales. American Journal of Botany 96: 296â322.
Rothwell GW, Nixon K. 2006. How does the inclusion of fossil data change our conclusions about the phylogenetic history of the euphyllophytes? International Journal of Plant Sciences 167: 737â749.
Rothwell GW, Stockey RA. 2016. Phylogenetic diversification of Early Cretaceous seed plants: The compound seed cone of Doylea tetrahedrasperma. American Journal of Botany 103: 923â937.
Schliep K, Potts AJ, Morrison DA, Grimm GW. 2017. Intertwining phylogenetic trees and networks. Methods in Ecology and Evolution DOI:10.1111/2041-210X.12760.
|Cichlids, species and trees||Lake Malawi, in south-eastern Africa, is famous for its large diversity of cichlid fishes. Indeed, it sometimes seems to have more biologists studying these fish than there are actual fish in the lake, even though there are allegedly hundreds of cichlid fish species in that lake. In this sense, it is somewhat similar to Lake Baikal, in southern Siberia, home to the sole species of freshwater seals.|
The cichlid biologists are interested in describing the extensive fish diversity, pondering its origin, and thus its contribution to the study of speciation. After all, we are talking about what is usually claimed to be "the most extensive recent vertebrate adaptive radiation". So, we are talking here as much about population genetics as we are about ichthyology.
Inevitably, the genome biologists have been spotted in the vicinity of the lake; and we now have a preliminary report from them:
Milan Malinsky, Hannes Svardal, Alexandra M. Tyers, Eric A. Miska, Martin J. Genner, George F. Turner, Richard Durbin (2017) Whole genome sequences of Malawi cichlids reveal multiple radiations interconnected by gene flow. BioRxiv 143859.These authors summarize the situation like this:
We characterize [the] genomic diversity by sequencing 134 individuals covering 73 species across all major lineages. Average sequence divergence between species pairs is only 0.1-0.25%. These divergence values overlap diversity within species, with 82% of heterozygosity shared between species. Phylogenetic analyses suggest that diversification initially proceeded by serial branching from a generalist Astatotilapia-like ancestor. However, no single species tree adequately represents all species relationships, with evidence for substantial gene flow at multiple times.The last sentence seems to be somewhat disingenuous. How could a single tree be expected to describe this scale of biodiversity? Any rapid radiation of diversity is unlikely to be completely tree-like. The increase in diversity can be modeled as a tree, sure, but it is very unlikely that there will be instant separation of the taxa, and so the tree model will be ignoring a large part of the evolutionary action. There will, for example, be ongoing introgression between the diverging taxa, as well as hybridization due to incomplete breeding barriers. These avenues for gene flow can best be modeled as a network, not a tree.
The issue here is that the authors write the paper solely from the perspective of an expected phylogenetic tree, and then feel compelled to explain why they do not produce such a tree. Indeed, the authors present their paper as a study of "violations of the species tree concept".
For data analysis, they proceed as follows:
To obtain a first estimate of between-species relationships we divided the genome into 2543 non-overlapping windows, each comprising 8000 SNPs (average size: 274kb), and constructed a Maximum Likelihood (ML) phylogeny separately for each window, obtaining trees with 2542 different topologies.So, only two sequence blocks produced the same tree, presumably by random chance. An example "tree" for 12 OTUs is shown in the diagram. It superimposes a possible mitochondrial trees on a summary of the "genome tree".
The authors continue:
The fact that we are using over 25 million variable sites suggests these differences are not due to sampling noise, but reflect conflicting biological signals in the data. For example, gene flow after the initial separation of species can distort the overall phylogeny and lead to intermediate placement of admixed taxa in the tree topology.Note that gene flow is seen to "distort" the phylogeny rather than being an integral part of it. In this case, "phylogeny" apparently refers solely to the diversification part evolutionary history, rather than to the whole history.
The ultimate questions from this paper are: "what is a species concept?", and "what is a species tree?". The authors write a lot about species and trees, and yet their data provide very clear evidence that both "species" and "tree" are very restrictive concepts for studying the cichlids of Lake Malawi.
Coincidentally, another recent paper tackles the same problems:
Britta S. Meyer, Michael Matschiner, Walter Salzburger (2017) Disentangling incomplete lineage sorting and introgression to refine species-tree estimates for Lake Tanganyika cichlid fishes. Systematic Biology 66: 531-550.The authors describe their work, on the same fish group but in a lake further north-west, as follows:
Because of the rapid lineage formation in these groups, and occasional gene flow between the participating species, it is often difficult to reconstruct the phylogenetic history of species that underwent an adaptive radiation. In this study, we present a novel approach for species-tree estimation in rapidly diversifying lineages, where introgression is known to occur, and apply it to a multimarker data set containing up to 16 specimens per species for a set of 45 species of East African cichlid fishes (522 individuals in total), with a main focus on the cichlid species flock of Lake Tanganyika. We first identified, using age distributions of most recent common ancestors in individual gene trees, those lineages in our data set that show strong signatures of past introgression ... We then applied the multispecies coalescent model to estimate the species tree of Lake Tanganyika cichlids, but excluded the lineages involved in these introgression events, as the multispecies coalescent model does not incorporate introgression. This resulted in a robust species tree.Once again, phylogeny = species tree.
|Bayesian inference of phylogenetic networks|
Over the years, a number of methods have been explored for constructing evolutionary networks, starting with parsimony criteria for optimization, and moving on to likelihood-based inference. However, the development of Bayesian methods has been somewhat delayed by the computational complexities involved.
The earliest work on this topic seems to be the thesis of:
Rosalba Radice (2011) A Bayesian Approach to Phylogenetic Networks. PhD thesis, University of Bath, UK.Apparently, the only part of this work to be published has been:
Rosalba Radice (2012) A Bayesian approach to modelling reticulation events with application to the ribosomal protein gene rps11 of flowering plants. Australian & New Zealand Journal of Statistics 54: 401-426.The method described requires the prior specification of the species tree (phylogeny), and the position and number of the reticulation events. The algorithm was implemented in the R language.
More recently, methods have been developed that infer phylogenies by using (i) incomplete lineage sorting (ILS) to model gene-tree incongruence arising from vertical inheritance, and (ii) introgression / hybridization to model gene-tree incongruence attributable to horizontal gene flow. ILS has been addressed using the multispecies coalescent.
The first of these publications was:
Dingqiao Wen, Yun Yu, Luay Nakhleh (2016) Bayesian inference of reticulate phylogenies under the multispecies network coalescent. PLoS Genetics 12(5): e1006006. [Correction: 2017 PLoS Genetics 13(2): e1006598]The method requires the set of gene trees as input, along with the number of reticulations. The algorithm was implemented in the PhyloNet package.
In the past few months, two manuscripts have appeared that try to co-estimate the gene trees and the species network, using the original sequence data (assumed to be without recombination) as input:
Dingqiao Wen, Luay Nakhleh (2017) Co-estimating reticulate phylogenies and gene trees from multi-locus sequence data. bioRxiv 095539. [v.2; v.1: 2016]
Chi Zhang, Huw A Ogilvie, Alexei J Drummond, Tanja Stadler (2017) Bayesian inference of species networks from multilocus sequence data. bioRxiv 124982.The algorithm for the first method has been implemented in the PhyloNet package, while the second has been implemented in the Beast2 package.
Finally, another manuscript describes a method utilizing data based on single nucleotide polymorphisms (SNPs) and/or amplified fragment length polymorphisms (AFLPs), which thus sidesteps the assumption of no recombination:
Jiafan Zhu, Dingqiao Wen, Yun Yu, Heidi Meudt, Luay Nakhleh (2017) Bayesian inference of phylogenetic networks from bi-allelic genetic markers. bioRxiv 143545.This method has also been implemented in PhyloNet.
Due to the computational complexity of likelihood inference, all of these methods are currently severely restricted in the number of OTUs that can be analyzed, irrespective of whether these involve multiple samples from the same species or not. In this sense, parsimony-based inference or approximate likelihood methods are still useful for constructing evolutionary networks of any size. However, progress is clearly being made to alleviate the computational restrictions.
|A test case for phylogenetic methods and stemmatics: the Divine Comedy|
In a previous post I gave an outline of stemmatics, and briefly touched on the adoption and advantages of phylogenetic methods for textual criticism (On stemmatics and phylogenetic methods). Here I present the results of an empirical investigation I have been conducting, in which such methods are used to study some philological dilemmas of a cornerstone work in textual criticism, Dante Alighieri's Divine Comedy. I am reproducing parts of the text and the results of a paper still under review; the NEXUS file for this research is available on GitHub.
Before describing the analysis, I discuss the work and its tradition, as well as some of the open questions concerning its textual criticism. This should not only allow the main audience of this blog to understand (and perhaps question) my work, but it is also a way to familiarize you with the kind of research conducted in stemmatics. After all, the first step is the recensio, a deep review of all information that can be gathered about a work.
The Divine Comedy
The Divine Comedy is an Italian medieval poem, and one of the most successful and influential medieval works. It is written in a rigid structure that, when compared to other works, guaranteed it a certain resistance to copy errors, as most changes would be immediately evident. Composed of three canticas (Inferno, Purgatory, and Paradise), the first of its 100 cantos were written in 1306-07, with the work completed not long before the death of the author in 1321. Written mostly during Dante's exile from his home city, Florence (Tuscany), like many works of the time it was published as the author wrote it, and not only upon completion. In fact, it is even possible, while not proven, that the author changed some cantos and published revisions, thus being himself the source of unresolvable differences.
No original manuscript has survived, but scholarship has traced the development of the tradition from copies and historical research. The poem is one of the most copied works of the Middle Ages, with more than 600 known complete copies, besides 200 partial and fragmentary witnesses. For of comparison, there are around 80 copies of Chaucer's Canterbury Tales,which is itself a successful work by medieval standards
Commercial enterprises soon developed to attend the market demand of its success. In terms of geographical diffusion, quantitative data suggests that, before the Black Death that ravaged the city of Florence in 1348, scribal activity was more intense in Tuscany than in Northern Italy, where the author had died. Among the hypotheses for its textual evolution, the results of my investigation support the widespread hypothesis that Dante published his work with Florentine orthography in Northern Italy. That is, the first copies adopted Northern orthographic standards, which would then revert to Tuscan customs, with occasional misinterpretations, when the work found its way back to Florence. These essentials of the transmission must be considered when curating a critical edition, as the less numerous Northern manuscripts, albeit with an adapted orthography, can in general be assumed to be closer to the archetype (if there ever was one to speak of) than Florentine ones.
The tradition is characterized by intentional contamination, as the work soon became a focus of politics and grammar prescriptivism. Errors and contamination have already been demonstrated in the earliest securely dated manuscript, the Landiano of 1336 (cf. Shaw, 2011), and can be already identified in the first commentaries dating from the 1320s (such as in the one by Jacopo Alighieri, the author's son).
Here are some details about previous studies. I have included considerable stemmatic information, but I include a biological analogy to help make sense for non-experts.
The first critical editions date from the 19th century, but a stemmatic approach would only be advanced at the end of that century, by Michele Barbi. Facing the problem of applying Lachmann's method to a long text with a massive tradition, in 1891 Barbi proposed his list of around 400 loci (samples of the text), inviting scholars to contribute the readings in the manuscripts they had access to. His project, which intended to establish a complete genealogy without the need for a full collatio, had disappointing results, with only a handful of responses. Mario Casella would later (1921) conduct the first formal stemmatic study on the poem, grouping some older manuscripts in two families, Î± and Î², of unequal number of witnesses but equal value for the emendatio. His two families are not rooted at a higher level, but he observed that they share errors supporting the hypothesis of a common ancestor, likely copied by a Northern scribe.
Forty years later, Giorgio Petrocchi proposed to overcome the large stemma by employing only witnesses dating from before the editorial activity of Giovanni Boccaccio, as his alterations and influence were considered to be too pervasive. Petrocchi defended a cut-off date of 1355 as being necessary for a stemmatic approach that would otherwise have been impossible, given the level of contamination of later copies. The restriction in the number of witnesses was contrasted by his expansion of the collatio to the entire text, criticizing Barbi's loci as subjective selections for which there was no proof of sufficiency.
Making use of analogies with biology, we may say that Barbi proposed to establish a tree from a reduced number of "proteins" for all possible "taxa". Casella considered this to be impracticable and, selecting a few representative "fossils", built a tree from a large number of phenotypic characteristics. Finally, Petrocchi produced a network while considering the entire "genome" for all "fossils" dated from before an event that, while well-supported in theory (we could compare its effects to a profound climate change), was nonetheless arbitrary.
Questions about Petrocchi's methodology and assumptions were soon raised, particularly regarding the proclaimed influence of Boccaccio, without quantitative proofs either that his editions were as influential as asserted or that all later witnesses were superfluous for stemmatics. Later research focused on questioning his stemma. For example, the absence of consensus about the relationship between the Ash and Ham manuscripts, the supposedly weak demonstration of the polytomy of Mad, Rb, and Urb (the "Northern manuscripts"), and the dating of Gv (likely copied fifty to a hundred years after Petrocchi's assumption). Evidence was presented that Co, a key manuscript in his stemma, could not be an ancestor of Lau (its copyist was still active in the 15th century), and that Ga contained disjunctive errors not found in its supposed decedents. Abusing once more of the biological analogy, the dating of his "fossils" was in some cases plainly wrong.
Federico Sanguineti presented an alternative stemma in 2001, arguing that a rigorous application of stemmatics would evidence errors in Petrocchi. To that end, he decided to resurrect Barbi's loci and trace the first complete genealogy, without arbitrary and a priori decisions about the usefulness of the textual witnesses. Sanguineti defended the suggestion that, after this proper recensio, a small number of manuscripts (which he eventually set to seven) would be sufficient for emendation. His stemma, described as "optimistic in its elegance and minimalism" (Shaw 2011), resulted in a critical edition that heavily relied in a single manuscript, Urb, the only witness of his Î² family (as Rb was displaced from the proximity it had in Petrocchi's stemma, and Mad was excluded from the analysis). Keeping with the biological analogy, he proposed building a tree from an extremely reduced number of "proteins", but for all "taxa". In the end, however, the reduced number of "proteins" was considered only for seven "taxa", selected mostly due to their age.
The edition of Sanguineti was attacked by critics, who confronted the limited number of manuscripts used in the emendatio, the position of Rb, the high value attributed to LauSC, and the unparalleled importance of Urb, all resulting in an unexpected Northern coloring to the language of a Florentine writer. Regarding his methodology, reviewers pointed out that stemmatic principles had not been followed strictly, as the elimination was not restricted to descripti, but extendied to branches that were considered to be too contaminated
The digital edition of Prue Shaw (2011) was developed as a project for phylogenetic testing of Sanguineti's assumptions. Her edition includes complete manuscript transcriptions, and the transcriptions include all of the layers of revision of each manuscript (original readings and corrections by later hands), and are complemented by high-quality reproductions of the manuscripts. After testing the validity of Sanguineti's method and stemma, Shaw concluded that his claims do not "stand up to close scrutiny", and that the entire edition is compromised, because Rb "is shown unequivocally to be a collaterale of Urb, and not a member of Î± as [Sanguineti] maintains".
Applying phylogenetic methods
With the goal of following and, to a large part, replicating Shaw (2011), I have analyzed signals of phylogenetic proximity for validating stemmatic hypotheses, produced both a computer-generated and a computer-assisted phylogeny (equivalent to a stemma), and evaluated the performance of suchphylogenies with methods of ancestral state reconstruction.
I wanted to investigate the proximity of witnesses and the statistical support for the published stemmas. After experiments with rooted graphs, I made a decision to use NeighborNets, in which splits are indicative of observed divergences and edge lengths are proportional to the observed differences. These unrooted split networks were preferable because they facilitated visual investigation, and also provided results for the subsequent steps. These involved exploring the topology and evaluating potential contaminations, guiding the elimination of taxa whose data would be redundant for establishing prior hypotheses on genealogical relationships. Analyses were conducted using all manuscript layers and critical editions, both with and without bootstrapping, thus obtaining results supported in terms of inferred trees as well as of character data.
The analysis confirmed most of the conclusions of Shaw (2011) â there are no doubts about the proximity and distinctiveness of Ash and Ham, with Sanguineti's hypothesis (in which they are collaterals) better supported than Petrocchi's hypothesis (in which the first is an ancestor of the second). The proximity of Mart and Triv was confirmed; but the position of the ancestors postulated by Petrocchi and Sanguineti should be questioned in face of the signals they share with LauSC, perhaps because of contamination. The most important finding, in line with Shaw and in contrast with the fundamental assumption of Sanguineti, is the clear demonstration of the relationship between Rb and Urb.
The relationship analyses allowed the generation of trees for further evaluation. Despite the goal of a full Bayesian tree-inference, I discarded that option because, without a careful and demanding selection of priors, it would yield flawed results. As such, I made the decision to build trees using both stochastic inference and user design (ie. manually). This postponed more complex topology analyses for future research, but generated the structures needed by the subsequent investigation steps; both trees are included in the datafile.
The second tree (shown below), allowing polytomies and manually constructed by myself, tries to combine the findings of Petrocchi and Sanguineti by resolving their differences with the support of the relationship analyses. Using Petrocchi's edition as a gold standard, and considering only single hypothesis reconstructions, parsimonious ancestral state reconstruction agree with 9,016 characters (79.9%). When considering multiple hypotheses, instead, reconstructions agree with 10,226 characters (90.7%). Cases of disagreement were manually analyzed and, as expected, most resulted from readings supported by the tradition but refuted by Petrocchi on exegetic grounds.
This tree suggests that, in general, Petrocchi's network is better supported than the tree by Sanguineti, as phylogenetic principles lead us to expect â the first was built considering statistical properties and using all of available data, while the second relied in many intuitions and hypothesis never really tested. In particular, it supports the findings of Shaw and, as such, allows us to indicate the critical edition of Petrocchi as the best one. Even more important, however, it is a further evidence of the usefulness of phylogenetic methods, when appropriately used, in stemmatics.
Alagherii, Dantis (2001) ComedÃ¬a. Edited by Federico Sanguineti. Firenze: Edizioni del Galluzzo.
Alighieri, Dante (1994) La Commedia Secondo Lâantica Vulgata: Introduzione. Edited by Giorgio Petrocchi. Opere di Dante Alighieri v. 1. Firenze: Le Lettere.
Huson, Daniel H.; Bryant, David (2006) Application of phylogenetic networks in evolutionary studies. Molecular Biology and Evolution 23: 254â267.
Inglese, Giorgio (2007) Inferno, Revisione del testo e commento. Roma: Carocci.
Kreft, Lukasz; Botzki, Alexander; Coppens, Frederik; Vandepoele, Klaas; Van Bel, Michiel (2017) PhyD3: a Phylogenetic Tree Viewer with Extended PhyloXML Support for Functional Genomics Data Visualization. BioRxiv. Doi: 10.1101/107276.
Leonardi, Anna M.C. (1991) Introduzione. In: La Divina Commedia, by Dante Alighieri. Milano: Arnoldo Mondadori Editore.
Shaw, Prue (2011) Commedia: a Digital Edition. Birmingham: Scholarly Digital Editions.
Trovato, Paolo (2016) Metodologia editoriale per la Commedia di Dante Alighieri. Ferrara. https://www.youtube.com/watch?v=BfKUOAR9PXA. Date of access: March 19, 2017.
|âIngredients in Victoriaâs Secret Bombshell and Ivanka Trump eaux de parfums that repel mosquitoesâ [research study]||Humanity’s war against mosquitoes still rages, after the failure of another new strategy. This study gives details of the failure: “Ingredients in Victoria’s Secret Bombshell and Ivanka Trump eaux de parfums that repel mosquitoes,” FangfangÂ Zeng,Â PingxiÂ Xu,Â KaimingÂ Tan,Â PauloÂ Zarbin,Â WalterÂ Leal, BioRxiv, August 3, 2017, doi.org/10.1101/172304. The authors, at the University of California Davis and Universidade Federal do ParanÃ¡, Brazil,Â report: “We […]|
|Science to Participate in bioRxivâs Manuscript Transfer Service||
Authors will have the opportunity to submit their manuscripts directly for consideration to Science.
|Authorea and BioRxiv Partner to Bring Preprints into 21st Century||
Authorea, the collaborative document editor for researchers, announced a partnership and direct submission agreement with bioRxiv, the leading preprint server for biological research.
|Comment on Protocols.io Tools for PLOS Authors: Reproducibility and Recognition by Lenny Teytelman||Dear Dr. Eysenbach,
Our protocols.io is not a journal but a repository. Like Dryad for data or GitHub for code, we are a repository for protocols that accompany published papers. We are also like bioRxiv for protocol preprints.
We do not do peer review and are not a journal. We are not in competition with your JRP, Nature Protocols, Current Protocols, Nature Methods, MethodsX, Bio-protocol, or any of the other method-centered journals.
|#ASAPbio and bioRxiv|
Back in 2013, the researchers at Cold Spring Harbor Laboratory decided to emulate the physicists using arXiv and create a pre-print repository for biological papers. They called it bioRxiv. Use increased slowly, for several reasons. Biologists didn’t want their work … Continue reading
|Shannonâs paper available as preprint||The lab’s latest manuscript is out for peer review. Before it is accepted for publication, you can read the preprint here. Congrats to Shannon and the lab for some great work! Let’s hope the reviewers agree. For more info on preprints, click here for bioRxiv, the preprint server for biology.|
|Comment on Rewiring Neuroscience: Letter To A Young Researcher by Benyamin||All very good points, though it does seem like there is a growing movement away from the old publishing model through platforms like http://www.biorxiv.org/.
Hopefully it is the start of a more open and collaborative publishing model.|
|TWiV 410: Hurricane Zika|
Sharon and ScottÂ join the TWiVÂ teamÂ to talk about their work on dengue antibody-dependent enhancement of Zika virus infection, and identifying the virus in mosquitoes from Miami.
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This episode is also brought to you by Drobo, a family of safe, expandable, yet simple to use storage arrays. Drobos are designed to protect your important data forever. VisitÂ www.drobo.comÂ to learn more. Listeners can save $100 on a Drobo system atÂ drobostore.comÂ by using the discount code Microbe100.
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SharonÂ -Â Zika virus comics and cartoonsÂ andÂ Florida weekly arbovirus reports
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|TWiV 399: Zika la femme|
The latest Zika virus news from the ConTWiVstadors, including a case of female to male transmission, risk of infection at the 2016 summer Olympics, a DNA vaccine, antibody-dependent enhancement by dengue antibodies, and sites of replication in the placenta.
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AlanÂ - CDC postmortem on Ebolavirus outbreak
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|TWiV 388: What could possibly go wrong?|
Preprint servers, the structure of an antibody bound to Zika virus, blocking Zika virus replication in mosquitoes with Wolbachia, and killing carp in Australia with a herpesvirus are topics of this episode hosted by Vincent, Dickson, Alan, and Kathy.
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|TWiV 387: Quaxxed|
Guest:Â Nina Martin
Nina Martin joinsÂ the TWiV team to talk about the movie Vaxxed, her bout with dengue fever, and the latest research on Zika virus.
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NinaÂ - Vaccines and Your Child by Paul Offit and
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|TWiV 367: Two sides to a Coyne|
Two Coynes join the TWiV overlords to explain theirÂ three-dimensional culture model of polarized intestinal cells for studying enterovirus infection.
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Kathy -Â Tardigrade genome sequence (video)
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|H11 Newsletter, Volume 1, Issue 2, 2017|
Volume 1 Issue 2 2017
Table of Contents
2. FT DNA Project
3. Project Statistics
4. Family Finder
5. Upgrading of reports by FT DNA
6. Recent publication â The Genetic History of Northern Europe, Mittnik et al
7. Blood of the Isles Database â Dr. Bryan Sykes
8. Genetic Genealogy in Practice, Blaine T Bettinger and Debbie Parker Wayne
When I introduced the H11 Newsletter in February 2011 I was not sure whether I would try for twice a year or four times per year. I have decided that visiting and reviewing the project four times a year is probably better and I will attempt to stay with that schedule. Any items of interest to members of the H11 haplogroup for submission in this newsletter please submit to Elizabeth Kipp (firstname.lastname@example.org) .
2. FT DNA Project:
There are now 221 members in our H11 project. Full sequence results are completed on 195 members of the group. There are some members who have not taken any mtDNA tests but I have not removed them from the project as eighteen of them have tested with the Genographic Project but not yet at FT DNA. There are six kits recently purchased not yet returned.
3. Project Statistics (yDNA statistics removed):
4. Family Finder:
Family Finder Results within the Project may well prove to be interesting but privacy concerns prevents me from sharing any of these results with the group. However, you are able to go into your own projects and see the Family Finder Results that you have.
5. Upgrading of reporting by FT DNA:
Within the study group we have members in every sub-haplogroup except H11a5 (and it can be seen in the chart above that the mutation C15040T marks this subgrouping). It is very helpful that FT DNA has now started to assign members based on this version of the phylotree.
6. Recent publication â The Genetic History of Northern Europe, Mittnik et al.
Thank you to one of the members of our study who sent this link to me. With the Eupedia article the following mention of H11:
"H11 is found across most of northern, central and eastern Europe, but also in Central Asia, where it might have been propagated by the Indo-European migrations (see below). H11a was identified in a Mesolithic hunter-gatherer from the Narva culture in Lithuania by Mittnik et al."
7. Blood of the Isles Database â Dr. Bryan Sykes:
One of my first introductions to H11 was in the Blood of the Isles Database back in 2007. This database actually had two members who shared my mutations which prior to finding these entries I had only seen several matches that I shared on FT DNA. I am in the process of testing at Living DNA and knowing the locations for all of my lines back into the mid 1600s with the exception of my mtDNA line I am curious what I might discover. The location for the two samples in the Blood of the Isles Database was Argyllshire/Ayrshire, Scotland. Over the years I have found two other individuals who trace back to this area and share my mutations. A number of individuals who share these same mutations trace back to County Antrim, Ireland. One of these individuals is descendant of the group of emigrants who came with the Rev William Martin to the Carolinas in 1772 and have an ancestry that goes back to Agryllshire/Ayrshire.
8. Genetic Genealogy in Practice, Blaine T Bettinger and Debbie Parker Wayne:
A member of the study has mentioned this particular book (which I have also purchased and I am in the process of working my way through it) and on page 57-58 he brought to my attention âJames Lickâs mtHap Haplogroup Analysis toolâ and the website url dna.jameslick.com/mthap/ which may interest readers of this newsletter. The explanation of the colours and terminology, etc. :
You use this particular tool in conjunction with your FASTA file. If you have completed the complete genetic scan of the mitochondria then your FASTA file can be downloaded from your mtDNA â Results page, scroll down to the bottom of this page and on the lower right hand side âDownload FASTA File.â
Any submissions to this newsletter can be submitted to Elizabeth Kipp (email@example.com).
|Pemodelan sistem akar tumbuhan||Buat ibu dan bapak dari ilmu hayati, berikut artikel tentang piranti lunak pemodelan sistem akar tumbuhan yang ditulis sebagai preprint di server BiorXivÂ (tautan). Time/date stampÂ (penanda waktu unggah) yang ada di bagian header adalah salah satu penangkal upaya scoopingÂ (duplikasi ide) secara disengaja. Terkait dengan naskah preprint di atas, si penulis juga mengunggah basis datanya secara daring … Continue reading Pemodelan sistem akar tumbuhan |
|TWiM #157: Back to the ancestor|
The TWiMbionts explore the role of bacteria in the genesis of moonmilk, and how ancient host proteins can be used to engineer resistance to virus infection.
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|TWiM #153: Covert pathogenesis|
The TWiM team ventures into preprint space with an analysis of type VI secretion across human gut microbiomes, and provide insight into urinary tract infection: how bladder exposure to a member of the vaginal microbiota triggers E. coli egress from latent reservoirs.
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Send your microbiology questions andÂ comments (email or recorded audio) to email@example.com
|TWiM #119: Power of one|
The microbophiles investigate the ratio of bacterial to human cells in our bodies, and how placing solar panels on a bacterium enables it to carry out photosynthesis.
Links for this episodeÂ
Music used on TWiM is composed and performed by Ronald Jenkees and used with permission.
Send your microbiology questions andÂ comments (email or mp3 file) to firstname.lastname@example.org.
Thumbnail image: Cell structure of a gram positive bacterium. This vector image is completely made by Ali Zifan - Own work; used information from Biology 10e Textbook (chapter 4, Pg: 63) by: Peter Raven, Kenneth Mason, Jonathan Losos, Susan Singer Â· McGraw-Hill Education.
|Dramatic Growth of Open Access June 30, 2017|| |
Correction: DOAJ will soon surpass 2.5 million articles, not a quarter of a billion as originally reported.
Open access continues to demonstrate robust growth on a global scale, in terms of works that are made available open access, ongoing growth in infrastructure (new repositories, journals, book publishers), strong growth for new initiatives such as SocArxiv, BioRxiv, the Directory of Open Access Books, SCOAP3, as well as ongoing strong growth in established services such as BASE, PubMed / PubMedCentral, Internet Archive (check out the new Collections including a Trump archive and FactChecker), DOAJ (almost 2.5 million articles searchable at the article level), RePEC and arXiv. Ongoing growth in infrastructure and OA policy give every reason to expect this growth to be ongoing.
Open Data Version
Morrison, Heather, 2014, "Dramatic Growth of Open Access", hdl:10864/10660, Scholars Portal Dataverse, V17,
This edition of the Dramatic Growth of Open Access highlights two of the new kids on the OA block - SocArxiv and BioRxiv, modeled on early OA success story arXiv, topping the quarterly growth by percentage with percentage growth of about 30% each! SocArxiv now has 1,200 documents and BioRxiv 12,800.
Similarly, a relative newcomer, the Directory of Open Access Books, is in both first and second place for annual growth by percentage with 68% growth for OA books and 40% of OA publishers in the past year for a total of 8,172 open access books and 217 OA book publishers.
SCOAP3, a global initiative to transform high-energy physics publishing to open access, is showing remarkable growth, 39% in the last year and 8% in the last quarter for a total of 15,790 articles funded.
To celebrate the growth of all OA services two pictures are presented of the growth of the largest collective OA search engine that I am aware of. Together, the 5,000 content providers who contribute metadata to the Bielefeld Academic Search Engine (BASE) have made available over 112 million documents. Around 60% of these are open access, so the number of OA documents in the world can be said to be somewhere about 67 million. BASE also posts their own online statistics table and chart - check it out here.
I wish I had the time to applaud and celebrate the growth of each and every OA service, but with 5,000 services contributing to BASE (and others that don't), if I worked on this 365 days a year I would have to cover 14 initiatives every day. So please feel free to help out by applauding and celebrating the services most relevant to you - the journals in your discipline, your institutional repository, the services you find most helpful to search.
Below you will find tables listing the top services by quarterly (5% or more) and annual growth (10% or more). For the full numbers download the open data version (link above). As usual Internet Archive is well represented, with 5 items in the list of the top 13 services by quarterly growth and the top 18 services by annual growth. Internet Archive also offers 2 intriguing new services under Collections - a Trump Archive with over a thousand videos and a Fact Checker collection with over 400 items, available at https://archive.org/details/tvhttps://archive.org/details/tv
Of course PubMed and PubMedCentral are up there in the growth charts, in this quarter for total number of items (5% quarterly growth) as well as what looks (to me) like hesitant new steps by a substantial number of journals, with a 26% increase in the number of contributing journals that provide some OA and a 14% increase in the number of journals that provide OA to selected articles. The number of journals providing immediate free access and/or all articles open access continues to increase, so this is clearly growth, not backsliding.
DOAJ is included in the top growth services with 14% growth in the number of articles searchable at article level. DOAJ now has over 2.49 million articles searchable at the article level and should soon surpass 2.5 million articles.
arXiv and RePEC are on the list for strong growth in articles, and ROARMAP for growth in OA policies.
This post is part of the Dramatic Growth of Open Access Series
Feel free to copy and share - with love. Note that images are compressed by the software to reduce file size, and they are also quickly outdated. You are welcome to use the images, but my recommendation is to download the data and make your own graphics. It's easier than you think with tools like modern spreadsheet software.
|Dramatic Growth of Open Access December 31, 2016||Download data here|
Bielefeld Academic Search Engine, which surpassed two major milestones in 2016: over 100 million documents (about 60% open access) and 5,000 content providers. The growth rates (22% for documents, 27% for content providers) are particularly impressive given the high pre-existing content rate. This is amazing success not just for BASE, but for all of us. If you've published a thesis through an institutional repository that allows for metadata harvesting, or published an article in a journal that contributes article-level data for metadata harvesting, your contribution is reflected here. This is a meta-level indicator of our global success.
I've added a new metric for medical open access, a keyword search of PubMed for "cancer" for articles with no date limit, last 5 years, last 2 years, and last year, further limited to free fulltext to determine the percentage of items for which fulltext is available. This ranges from 26% overall (no date limit), to 40 - 44% for items published in the last 2 - 5 years, to 32% for articles published in the last year.
Also added this quarter: OECD iLibrary - with more than 11,000 free books, this one publisher's OA collection is nearly double the size of the 167 publishers included in the impressivley growing Directory of Open Access Books! arXiv, in addition to an over 10% growth rate last year, inspired the recent development of two similar services, socArXiv and bioRxiv, newly added to facilitate future growth tracking. The DOAJ get-tough inclusion policy and March 2016 major weeding means the DOAJ count for titles, countries and journals searchable at the article level are all down from last year, while articles searchable at the article level through DOAJ continued to show robust growth of 13%. DOAJ's quarterly growth is back to an impressive rate of just under 3 titles per day. RePEC surpassed a milestone of 2 million downloadable items this year, while Internet Archive surpassed 3 milestones: there are now more than 3 million video and audio recordings, and more than 11 million texts (the number of IA web pages archived is way down, by the billions - such a difference it strikes me as likely due to a glitch in counting, whether before or after). Recently Open Journal Systems announced that OJS is now used by more than 10,000 active journals which <
Kudos and thanks to everyone in the open access movement - every researcher, author, editor, publisher, archive manager, librarian, policy-maker, and activist who is making open access happen. What of 2017? My advice: let's remember the beautiful vision of the potential unprecedented public good of open access - forged not at a time of peace and certainty, but rather within months of the trauma of 9/11 - repeated below - and keep on making it happen.
An old tradition and a new technology have converged to make possible an unprecedented public good. The old tradition is the willingness of scientists and scholars to publish the fruits of their research in scholarly journals without payment, for the sake of inquiry and knowledge. The new technology is the internet. The public good they make possible is the world-wide electronic distribution of the peer-reviewed journal literature and completely free and unrestricted access to it by all scientists, scholars, teachers, students, and other curious minds. Removing access barriers to this literature will accelerate research, enrich education, share the learning of the rich with the poor and the poor with the rich, make this literature as useful as it can be, and lay the foundation for uniting humanity in a common intellectual conversation and quest for knowledge.
Selected numbers and growth by service:
Directory of Open Access Journals
Highlights: in March 2016 DOAJ removed more than 3,000 journals, reflecting a new get-tough inclusion policy. All journals that had not gone through DOAJ's new application process were removed. As a result, in spite of robust quarter since the removal process, most of DOAJ's key data are lower at the end of 2016 than at 2015, with the exception of number of articles searchable through DOAJ which grew by 13%.
3,000 repository milestone!!!
100 million document milestone!!!
5,000 content providers milestone!!!
4 million article milestone!!!
(in beta December 31, 2016, inspired by arXiv) ***
2 million downloadable items milestone!!!
3 million milestones for video and audiorecordings!!!
10 million milestone for texts (now 11 million)!!!
* OECD iLibrary statement on free-to-read (from About page):
All book and journal content is available to all users to read online by clicking the READ icon. Read editions are optimised for browser-enabled mobile devices and can be read online wherever there is an internet connection - desktop computer, tablets or smart phones. They are also shareable and embeddable.** about SocArXiv (from the Dec. 7, 2016 launch announcement):
SocArXiv, the open access, open source archive of social science, is officially launching in beta version today. Created in partnership with the Center for Open Science, SocArXiv provides a free, noncommercial service for rapid sharing of academic papers; it is built on the Open Science Framework, a platform for researchers to upload data and code as well as research results*** about bioRxiv (from about page):
bioRxiv (pronounced "bio-archive") is a free online archive and distribution service for unpublished preprints in the life sciences. It is operated by Cold Spring Harbor Laboratory, a not-for-profit research and educational institution. By posting preprints on bioRxiv, authors are able to make their findings immediately available to the scientific community and receive feedback on draft manuscripts before they are submitted to journals.This post is part of the Dramatic Growth of Open Access series.
|uBiome Reveals Details of Clinical Screening Test for Gut Health|| |
uBiome, the leader in microbial genomics, has created an entirely new approach to support the clinical diagnosis of gut health conditions. The preprint of the publication in BioRxiv allows both citizen scientists and research scientists to have access the results of uBiomeâs research.
(PRWeb November 03, 2016)
Read the full story at http://www.prweb.com/releases/2016/11/prweb13821806.htm
|Biologists debate how to license preprints|
Biologists debate how to license preprints
Biologyâs zeal for preprints â papers posted online before peer review â is opening up a thorny legal debate: should scientists license their manuscripts on open-access terms? Researchers have now shared more than 11,000 papers at the popular bioRxiv preprints site. But where some researchers allow their bioRxiv manuscripts to be freely redistributed and reused, others have chosen to lock them down with restrictive terms.
|TelomereHunter: telomere content estimation and characterization from whole genome sequencing data||Lars Feuerbach, et al.,Â TelomereHunter: telomere content estimation and characterization from whole genome sequencing data, bioRxiv, 2016 Here, we present TelomereHunter, a new computational tool for determining telomere content that is specifically designed for matched tumor and control pairs. In contrast to existing tools, TelomereHunter takes alignment information into account and reports the abundance of variant […]|
|Our preprint on brain-heart communication in athletes and sedentary young adults, available for peer review||Our recent research, revealing significant differences in how the brains of physically trained and sedentary young adults process information from the heart, is now available for commentary and formal peer review in two preprint repositories: SJS (@social_sjs) and bioRxiv (@biorxivpreprint). Each of these repositories comes with advantages and disadvantages. BioRxiv is already backed by a … Continue reading "Our preprint on brain-heart communication in athletes and sedentary young adults, available for peer review"|
|MERS-CoV spillover at the camel-human interface||Via bioRxiv: MERS-CoV spillover at the camel-human interface. The update: Middle East respiratory syndrome coronavirus (MERS-CoV) is a zoonotic virus originating in camels that has been causing significant mortality and morbidity in humans in the Arabian Peninsula. The epidemiology of...|
|Making Sour Beer||The science of yeast fermentation in sour beer production is sophisticated stuff explored in a new preprint. There are hundreds of strains of beer yeast and some are particularly well suited to the task.|
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|BONUS: The Evolutionary Psychology of Mate Preference. 18 Jul 2017|
Earlier this year I posted a bonus episode featuring contributions from students in my undergraduate seminar here at Basel University. It proved to be one of the more popular episodes of the podcast. This semester I taught a masters level class on the evolutionary psychology of mate preference and, again, gave the students the task of summarising the research papers they found most interesting for a special bonus episode. As before, most of the students are not native English speakers, nor have they recorded audio before. I am super grateful they agreed to be a part of the podcast (especially after I freaked them out by telling them how many people listened to the previous bonus episode!).
Mittlere Rheinbruecke, Basel. Mariano Mantel/Flickr
The articles covered in the show (in order of appearance):
|Pride and Prejudice and journal citation distributions: final, peer reviewed version||Today sees the publication on bioRxiv of a revised version of our preprint outlining âA simple proposal for the publication of journal citation distributions.â OurÂ proposal, explained in more detail in this earlier post, encourages publishers to mitigate the distorting effects … Continue reading |
|Why Elephants Donât Get Cancer|
Being an elephant is risky business. I'm not talking about poaching, habitat loss, or fighting with males in musthâI'm talking about the simple fact of living. Every time an elephant cell divides, it runs the risk of going haywire and developing into an out-of-control tumor. Since elephants have 100 times the number of cells that human beings do, they should have 100 times the risk of getting cancer. That's a lot of mistakes waiting to happen.
In reality, given their size and prodigious lifespans, elephants have one of the lowest cancer mortality rates in the animal kingdom: 4.8 percent, compared to a range of 11 to 25 percent for humans. How can this be?
Scientists at the Huntsman Cancer Institute, University of Utah School of Medicine, and Primary Childrenâs Hospital helped figure out the answer, published Thursday in the Journal of the American Medical Association. Another team, made up of University of Chicago researchers and their colleagues, posted a related paper this week. As it turns out, elephants have developed some ingenious safeguards against developing cancer. Understanding their cellular protections might help us learn more about how to suppress cancer in humans.
There are countless ways that cell division can go wrong. Thatâs whyâas we learned from the winners of this weekâs Chemistry Nobel Prizeâyour cells come equipped with a host of repair enzymes whose sole purpose is to prevent or repair genetic mistakes. These cellular copy editors proofread each strand of newly divided DNA, identifying errors and repairing the faulty bits to ensure that your DNA stays fresh and clean and functional. In humans, just one of those enzymes can fix a thousand different kinds of errors. Not too shabby!
But elephants have one-upped us. For the JAMA study, researchers first compared cancer rates across the animal kingdom to find out that elephants were remarkably cancer-free given their size. (Other animals fared well, too. For comparison, rock hyraxes have a 1 percent cancer mortality rate, African wild dogs have an 8 percent rate, and lions have a 2 percent rate.) Then, they scoured the elephant genome to find out why.
The answer resided in a key tumor-suppressing protein called p53, known as the "guardian of the genome." Compared to humans, elephants had far more genes for this protein: 38 versions versus just two. The result was a superior genetic safety net for correcting errors and ensuring that damaged, tumor-prone cells get nipped in the bud. "The enormous mass, extended life-span, and reproductive advantage of older elephants would have selected for an efficient and fail-safe method for cancer suppression," the authors write.
To see how the genes suppressed tumors, researchers teamed up with Utahâs Hogle Zoo and Ringling Bros. Center for Elephant Conservation to isolate elephant cells and subject them to cancer triggers. (No elephants were harmed; this was all during routine wellness checks.) When they compared elephant cells to human cells, they found something amazing: The damaged cells in elephants were far more likely to resort to cell suicideâknown as apoptosisâto avoid propagating errors in their descendants. It was a brutally efficient, even ruthless, system for protecting the organism at all costs.
To behold an elephant in the wild is to be humbled before majesty. Yet perhaps it isn't just their tremendous size that contributes to this sense of smallness. It's also all the things we can't see: from their advanced memories, to their long lifespans, to their individual cells, so altruistic that they are willing to die for the benefit of the many. From these cancer-resistant Methuselahs, we humans have much to learn.
|The Big Ideas in Cognitive Neuroscience, Explained|
Are emergent properties really for losers? Why are architectures important? What are âmirror neuron ensemblesâ anyway? My last post presented an idiosyncratic distillation of the Big Ideas in Cognitive Neuroscience symposium, presented by six speakers at the 2017 CNS meeting. Here Iâll briefly explain what I meant in the bullet points. In some cases I didn't quite understand what the speaker meant so I used outside sources. At the end is a bonus reading list.
The first two speakers made an especially fun pair on the topic of memory: they held opposing views on the âengramâ, the physical manifestation of a memory in the brain.1 They also disagreed on most everything else.
1. Charles Randy Gallistel (Rutgers University) â What Memory Must Look Like
Gallistel is convinced that Most Neuroscientists Are Wrong About the Brain. This subtly bizarre essay in Nautilus (which was widely scorned on Twitter) succinctly summarized the major points of his talk. You and I may think the brain-as-computer metaphor has outlived its usefulness, but Gallistel says that âComputation in the brain must resemble computation in a computer.â
2. TomÃ¡s Ryan (@TJRyan_77) â Information Storage in Memory Engrams
Ryan began by acknowledging that he had tremendous respect for Gallistal's speech â which was in turn powerful, illuminating, very categorical, polarizing, and rigid. But wrong. Oh so very wrong. Memory is not essentially molecular, we should not approach memory and the brain from a design perspective, and information storage need not mimic a computer.
Angela Friederici (Max Planck Institute for Human Cognitive and Brain Sciences) â Structure and Dynamics of the Language Network
Following on the heels of the rodent engram crowd, Friederici pointed out the obvious limitations of studying language as a human trait.
The problem is that acute stroke patients with dysfunctional tissue in left BA 44 do not have impaired syntax. Instead, they have difficulty with phonological short-term memory (keeping strings of digits in mind, like remembering a phone number).
âThis is a poor hypothesis,â she said.
Jean-RÃ©mi King (@jrking0) â Parsing Human Minds
King's expertise is in visual processing (not language), but his talk drew parallels between vision and speech comprehension. A key goal in both domains is to identify the algorithm (sequence of operations) that translates input into meaning.
Each architecture could be compatible with a pattern of brain activity at different time points. But do the classifiers at different time points generalize to other time points? This can be determined by a temporal generalization analysis, which âreveals a repertoire of canonical brain dynamics.â
Danielle Bassett (@DaniSBassett) â A Network Neuroscience of Human Learning: Potential to Inform Quantitative Theories of Brain and Behavior
Bassett previewed an arc of exciting ideas where we've shown progress, followed by frustrations and failures, which may ultimately provide an opening for the really Big Ideas. Her focus is on learning from a network perspective, which means patterns of connectivity in the whole brain. What is the underlying network architecture that facilitates the spatial distributed effects?
What is the relationship between these two notions of modularity?
[I ask this as an honest question.]
Major challenges remain, of course.
Incorporate well-specified behavioral models such as reinforcement learning and the drift diffusion model of decision making. These models are fit to the data to derive parameters such as the alpha parameter from reinforcement learning rate. Models of behavior can help generate hypotheses about how the system actually works.
Network models are extremely useful, but they're not theories. They're descriptors. They don't generate new frameworks for understanding what the data should look like. Theory-building is obviously critical for moving forward.
John Krakauer (@blamlab) â Big Ideas in Cognitive Neuroscience: Action
Krakauer mentioned the Big Questions in Neuroscience symposium at the 2016 SFN meeting, which motivated the CNS symposium as well as a splashy critical paper in Neuron. He raised an interesting point about how the term âconnectivityâ has different meanings, i.e. the type of embedded connectivity that stores information (engrams) vs. the type of correlational connectivity when modules combine with each other to produce behavior. [BTW, is everyone here using âmodulesâ in the same way?]
OVERALL, there was an emphasis on computational approaches with nods to the three levels of David Marr:
computation â algorithm â implementation
We know from from Krakauer et al. 2017 (and from CNS meetings past and present) that co-organizer David Poeppel is a big fan of Marr. The end goal of a Marr-ian research program is to find explanations, to reach an understanding of brain-behavior relations. This requires a detailed specification of the computational problem (i.e., behavior) to uncover the algorithms. The correlational approach of cognitive neuroscience â and even the causal-mechanistic circuit manipulations of optogenetic neuroscience â just don't cut it anymore.
1 Although neither speaker explicitly defined the term, it is most definitely not the engram as envisioned by Scientology: âa detailed mental image or memory of a traumatic event from the past that occurred when an individual was partially or fully unconscious.â The term was first coined by Richard Semon in 1904.
2 This paper (by Johansson et al, 2014) appeared in PNAS, and Gallistel was the prearranged editor.
3 For instance, here's Mu-ming Poo: âThere is now general consensus that persistent modification of the synaptic strength via LTP and LTD of pre-existing connections represents a primary mechanism for the formation of memory engrams.â
4 If you don't understand all this, you're not alone. From Machine Learning: the Basics.
This idea of minimizing some function (in this case, the sum of squared residuals) is a building block of supervised learning algorithms, and in the field of machine learning this function - whatever it may be for the algorithm in question - is referred to as the cost function.
Everyone is Wrong
Here's Why Most Neuroscientists Are Wrong About the Brain. Gallistel in Nautilus, Oct. 2015.
Time to rethink the neural mechanisms of learning and memory. Gallistel CR, Balsam PD. Neurobiol Learn Mem. 2014 Feb;108:136-44.
Engrams are Cool
What is memory? The present state of the engram. Poo MM, Pignatelli M, Ryan TJ, Tonegawa S, Bonhoeffer T, Martin KC, Rudenko A, Tsai LH, Tsien RW, Fishell G, Mullins C, GonÃ§alves JT, Shtrahman M, Johnston ST, Gage FH, Dan Y, Long J, BuzsÃ¡ki G, Stevens C. BMC Biol. 2016 May 19;14:40.
Engram cells retain memory under retrograde amnesia. Ryan TJ, Roy DS, Pignatelli M, Arons A, Tonegawa S. Science. 2015 May 29;348(6238):1007-13.
Engrams are Overrated
For good measure, some contrarian thoughts floating around Twitter...
âCan We Localize Merge in the Brain? Yes We Canâ
Merge in the Human Brain: A Sub-Region Based Functional Investigation in the Left Pars Opercularis. Zaccarella E, Friederici AD. Front Psychol. 2015 Nov 27;6:1818.
The neurobiological nature of syntactic hierarchies. Zaccarella E, Friederici AD. Neurosci Biobehav Rev. 2016 Jul 29. doi: 10.1016/j.neubiorev.2016.07.038.
Asyntactic comprehension, working memory, and acute ischemia in Broca's area versus angular gyrus. Newhart M, Trupe LA, Gomez Y, Cloutman L, Molitoris JJ, Davis C, Leigh R, Gottesman RF, Race D, Hillis AE. Cortex. 2012 Nov-Dec;48(10):1288-97.
Patients with acute strokes in left BA 44 (part of Broca's area) do not have impaired syntax.
Dynamics of Mental Representations
Characterizing the dynamics of mental representations: the temporal generalization method. King JR, Dehaene S. Trends Cogn Sci. 2014 Apr;18(4):203-10.
King JR, Pescetelli N, Dehaene S. Brain Mechanisms Underlying the Brief Maintenance of Seen and Unseen Sensory Information. Neuron. 2016; 92(5):1122-1134.
A Spate of New Network Articles by Bassett
A Network Neuroscience of Human Learning: Potential to Inform Quantitative Theories of Brain and Behavior. Bassett DS, Mattar MG. Trends Cogn Sci. 2017 Apr;21(4):250-264.
This one is most relevant to Dr. Bassett's talk, as it is the title of her talk.
Network neuroscience. Bassett DS, Sporns O. Nat Neurosci. 2017 Feb 23;20(3):353-364.
Emerging Frontiers of Neuroengineering: A Network Science of Brain Connectivity. Bassett DS, Khambhati AN, Grafton ST. Annu Rev Biomed Eng. 2017 Mar 27. doi: 10.1146/annurev-bioeng-071516-044511.
Modelling And Interpreting Network Dynamics [bioRxiv preprint]. Ankit N Khambhati, Ann E Sizemore, Richard F Betzel, Danielle S Bassett. doi: https://doi.org/10.1101/124016
Behavior is Underrated
Neuroscience Needs Behavior: Correcting a Reductionist Bias. Krakauer JW, Ghazanfar AA, Gomez-Marin A, MacIver MA, Poeppel D. Neuron. 2017 Feb 8;93(3):480-490.
The first author was a presenter and the last author an organizer of the symposium.
Thanks to @jakublimanowski for the tip on Goldstein (1999).