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Cited by 454

The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.

STEM: species tree estimation using maximum likelihood for gene trees under coalescence

Open access
Kubatko, Laura S., Carstens, Bryan C., Knowles, L. Lacey·2009·Bioinformatics

Abstract

Summary: STEM is a software package written in the C language to obtain maximum likelihood (ML) estimates for phylogenetic species trees given a sample of gene trees under the coalescent model. It includes options to compute the ML species tree, search the space of all species trees for the k trees of highest likelihood and compute ML branch lengths for a user-input species tree. Availability: The STEM package, including source code, is freely available at http://www.stat.osu.edu/~lkubatko/software/STEM/. Contact: lkubatko@stat.osu.edu Supplementary information: Supplementary data are available at Bioinformatics online.

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Registry

Crossref · 10.1093/bioinformatics/btp079

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Metadata

Authors
Kubatko, L. S., Carstens, B. C., & Knowles, L. L.
Venue
Bioinformatics
Published
2009-02-10
Volume
25
Issue
7
Pages
971-973
ISSN
  • 1367-4803 (ISSN-L)
  • 1367-4811
OpenAlex
W2114227052
Cited by
454
References
21
FWCI
14.88
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: STEM: species tree estimation using maximum likelihood for gene trees under coalescence. https://app.cochat.ai/papers/10.1093/bioinformatics/btp079
The paper
Kubatko, L. S., Carstens, B. C., & Knowles, L. L. (2009). STEM: species tree estimation using maximum likelihood for gene trees under coalescence. Bioinformatics. https://doi.org/10.1093/bioinformatics/btp079

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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.