Unsupervised machine learning for species delimitation, integrative taxonomy, and biodiversity conservation.

Saved in:
Bibliographic Details
Title: Unsupervised machine learning for species delimitation, integrative taxonomy, and biodiversity conservation.
Authors: Alexander Pyron R; Department of Biological Sciences, The George Washington University, Washington, DC 20052 USA. Electronic address: rpyron@colubroid.org.
Source: Molecular phylogenetics and evolution [Mol Phylogenet Evol] 2023 Dec; Vol. 189, pp. 107939. Date of Electronic Publication: 2023 Oct 05.
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Academic Press Country of Publication: United States NLM ID: 9304400 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1095-9513 (Electronic) Linking ISSN: 10557903 NLM ISO Abbreviation: Mol Phylogenet Evol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1095-9513
DOI:10.1016/j.ympev.2023.107939