The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
BEAGLE: An Application Programming Interface and High-Performance Computing Library for Statistical Phylogenetics
Open accessAbstract
Phylogenetic inference is fundamental to our understanding of most aspects of the origin and evolution of life, and in recent years, there has been a concentration of interest in statistical approaches such as Bayesian inference and maximum likelihood estimation. Yet, for large data sets and realistic or interesting models of evolution, these approaches remain computationally demanding. High-throughput sequencing can yield data for thousands of taxa, but scaling to such problems using serial computing often necessitates the use of nonstatistical or approximate approaches. The recent emergence of graphics processing units (GPUs) provides an opportunity to leverage their excellent floating-point computational performance to accelerate statistical phylogenetic inference. A specialized library for phylogenetic calculation would allow existing software packages to make more effective use of available computer hardware, including GPUs. Adoption of a common library would also make it easier for other emerging computing architectures, such as field programmable gate arrays, to be used in the future. We present BEAGLE, an application programming interface (API) and library for high-performance statistical phylogenetic inference. The API provides a uniform interface for performing phylogenetic likelihood calculations on a variety of compute hardware platforms. The library includes a set of efficient implementations and can currently exploit hardware including GPUs using NVIDIA CUDA, central processing units (CPUs) with Streaming SIMD Extensions and related processor supplementary instruction sets, and multicore CPUs via OpenMP. To demonstrate the advantages of a common API, we have incorporated the library into several popular phylogenetic software packages. The BEAGLE library is free open source software licensed under the Lesser GPL and available from http://beagle-lib.googlecode.com. An example client program is available as public domain software.
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
Evolutionary trees from DNA sequences: A maximum likelihood approach.
Felsenstein, J. (1981) · Journal of Molecular Evolution · doi:10.1007/bf01734359 · Cited by 14,571
Cited by
BEAST 2: a software platform for Bayesian evolutionary analysis
Bouckaert, R., Heled, J., Kühnert, D., Vaughan, T., Wu, C.-H., Xie, D., Suchard, M. A., Rambaut, A., & Drummond, A. J. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003537 · Cited by 6,527
Self-citationGenomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil
Faria, N. R., Mellan, T. A., Whittaker, C., Claro, I. M., Candido, D. D. S., Mishra, S., Crispim, M. A. E., Sales, F. C. S., Hawryluk, I., McCrone, J. T., et al. (2021) · Science · doi:10.1126/science.abh2644 · Cited by 1,461
Self-citationEvolution and epidemic spread of SARS-CoV-2 in Brazil
Candido, D. S., Claro, I. M., de Jesus, J. G., Souza, W. M., Moreira, F. R. R., Dellicour, S., Mellan, T. A., du Plessis, L., Pereira, R. H. M., Sales, F. C. S., et al. (2020) · Science · doi:10.1126/science.abd2161 · Cited by 573
Self-citationOude Munnink, B. B., Nieuwenhuijse, D. F., Stein, M., O’Toole, Á., Haverkate, M., Mollers, M., Kamga, S. K., Schapendonk, C., Pronk, M., Lexmond, P., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0997-y · Cited by 306
Self-citationLoci associated with skin pigmentation identified in African populations
Crawford, N. G., Kelly, D. E., Hansen, M. E. B., Beltrame, M. H., Fan, S., Bowman, S. L., Jewett, E., Ranciaro, A., Thompson, S., Lo, Y., et al. (2017) · Science · doi:10.1126/science.aan8433 · Cited by 321
Metadata
- Authors
- Ayres, D. L., Darling, A., Zwickl, D. J., Beerli, P., Holder, M. T., Lewis, P. O., Huelsenbeck, J. P., Ronquist, F., Swofford, D. L., Cummings, M. P., Rambaut, A., & Suchard, M. A.
- Venue
- Systematic Biology
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-10-01
- Volume
- 61
- Issue
- 1
- Pages
- 170-173
- ISSN
- 1063-5157 (ISSN-L)
- 1076-836X
- OpenAlex
- W2169981472
- Cited by
- 706
- References
- 1
- FWCI
- 8.82
- Type
- journal article
- Language
- en
- Open access
- hybrid
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
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.