The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Datamonkey 2.0: A Modern Web Application for Characterizing Selective and Other Evolutionary Processes
Open accessAbstract
Inference of how evolutionary forces have shaped extant genetic diversity is a cornerstone of modern comparative sequence analysis. Advances in sequence generation and increased statistical sophistication of relevant methods now allow researchers to extract ever more evolutionary signal from the data, albeit at an increased computational cost. Here, we announce the release of Datamonkey 2.0, a completely re-engineered version of the Datamonkey web-server for analyzing evolutionary signatures in sequence data. For this endeavor, we leveraged recent developments in open-source libraries that facilitate interactive, robust, and scalable web application development. Datamonkey 2.0 provides a carefully curated collection of methods for interrogating coding-sequence alignments for imprints of natural selection, packaged as a responsive (i.e. can be viewed on tablet and mobile devices), fully interactive, and API-enabled web application. To complement Datamonkey 2.0, we additionally release HyPhy Vision, an accompanying JavaScript application for visualizing analysis results. HyPhy Vision can also be used separately from Datamonkey 2.0 to visualize locally executed HyPhy analyses. Together, Datamonkey 2.0 and HyPhy Vision showcase how scientific software development can benefit from general-purpose open-source frameworks. Datamonkey 2.0 is freely and publicly available at http://www.datamonkey.org, and the underlying codebase is available from https://github.com/veg/datamonkey-js.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Goecks, J., Nekrutenko, A., Taylor, J., & The Galaxy Team (2010) · Genome Biology · doi:10.1186/gb-2010-11-8-r86 · Cited by 3,453
HyPhy: hypothesis testing using phylogenies
Pond, S. L. K., Frost, S. D. W., & Muse, S. V. (2005) · Bioinformatics · doi:10.1093/bioinformatics/bti079 · Cited by 2,866
Self-citationNot So Different After All: A Comparison of Methods for Detecting Amino Acid Sites Under Selection
Kosakovsky Pond, S. L., & Frost, S. D. W. (2005) · Molecular Biology and Evolution · doi:10.1093/molbev/msi105 · Cited by 2,324
Self-citationDetecting Individual Sites Subject to Episodic Diversifying Selection
Murrell, B., Wertheim, J. O., Moola, S., Weighill, T., Scheffler, K., & Kosakovsky Pond, S. L. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002764 · Cited by 1,811
FUBAR: A Fast, Unconstrained Bayesian AppRoximation for Inferring Selection
Murrell, B., Moola, S., Mabona, A., Weighill, T., Sheward, D., Kosakovsky Pond, S. L., & Scheffler, K. (2013) · Molecular Biology and Evolution · doi:10.1093/molbev/mst030 · Cited by 1,358
Self-citationDatamonkey: rapid detection of selective pressure on individual sites of codon alignments
Pond, S. L. K., & Frost, S. D. W. (2005) · Bioinformatics · doi:10.1093/bioinformatics/bti320 · Cited by 1,354
Automated Phylogenetic Detection of Recombination Using a Genetic Algorithm
Kosakovsky Pond, S. L., Posada, D., Gravenor, M. B., Woelk, C. H., & Frost, S. D. W. (2006) · Molecular Biology and Evolution · doi:10.1093/molbev/msl051 · Cited by 945
Self-citationSmith, M. D., Wertheim, J. O., Weaver, S., Murrell, B., Scheffler, K., & Kosakovsky Pond, S. L. (2015) · Molecular Biology and Evolution · doi:10.1093/molbev/msv022 · Cited by 811
Self-citationRELAX: Detecting Relaxed Selection in a Phylogenetic Framework
Wertheim, J. O., Murrell, B., Smith, M. D., Kosakovsky Pond, S. L., & Scheffler, K. (2015) · Molecular Biology and Evolution · doi:10.1093/molbev/msu400 · Cited by 778
Best Practices for Scientific Computing
Wilson, G., Aruliah, D. A., Brown, C. T., Chue Hong, N. P., Davis, M., Guy, R. T., Haddock, S. H. D., Huff, K. D., Mitchell, I. M., Plumbley, M. D., et al. (2014) · PLoS Biology · doi:10.1371/journal.pbio.1001745 · Cited by 723
Cited by
Kistler, K. E., & Bedford, T. (2021) · eLife · doi:10.7554/elife.64509 · Cited by 94
Evolutionary dynamics of the chromatophore genome in three photosynthetic Paulinella species
Lhee, D., Ha, J.-S., Kim, S., Park, M. G., Bhattacharya, D., & Yoon, H. S. (2019) · Scientific Reports · doi:10.1038/s41598-019-38621-8 · Cited by 54
Lignocellulose degradation in isopods: new insights into the adaptation to terrestrial life
Bredon, M., Herran, B., Lheraud, B., Bertaux, J., Grève, P., Moumen, B., & Bouchon, D. (2019) · BMC Genomics · doi:10.1186/s12864-019-5825-8 · Cited by 36
Schaschl, H., & Wallner, B. (2020) · BMC Evolutionary Biology · doi:10.1186/s12862-019-1575-0 · Cited by 24
Recognition and cleavage of human tRNA methyltransferase TRMT1 by the SARS-CoV-2 main protease
D'Oliviera, A., Dai, X., Mottaghinia, S., Olson, S., Geissler, E. P., Etienne, L., Zhang, Y., & Mugridge, J. S. (2025) · eLife · doi:10.7554/elife.91168.3 · Cited by 13
Metadata
- Authors
- Weaver, S., Shank, S. D., Spielman, S. J., Li, M., Muse, S. V., & Kosakovsky Pond, S. L.
- Venue
- Molecular Biology and Evolution
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-01-02
- Volume
- 35
- Issue
- 3
- Pages
- 773-777
- ISSN
- 0737-4038 (ISSN-L)
- 1537-1719
- OpenAlex
- W2781938185
- Cited by
- 983
- References
- 27
- FWCI
- 17.76
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Datamonkey 2.0: A Modern Web Application for Characterizing Selective and Other Evolutionary Processes. https://app.cochat.ai/papers/10.1093/molbev/msx335
- The paper
- Weaver, S., Shank, S. D., Spielman, S. J., Li, M., Muse, S. V., & Kosakovsky Pond, S. L. (2018). Datamonkey 2.0: A Modern Web Application for Characterizing Selective and Other Evolutionary Processes. Molecular Biology and Evolution. https://doi.org/10.1093/molbev/msx335
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.