An interpretable machine learning framework for dog breed inference and ancestry decomposition.

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Bibliographic Details
Title: An interpretable machine learning framework for dog breed inference and ancestry decomposition.
Authors: Bian Y; Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, South Drive, Princeton University, Princeton, NJ 08544, USA., Bierman R; Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, South Drive, Princeton University, Princeton, NJ 08544, USA., Snyder-Mackler N; Center for Evolution & Medicine, Arizona State University; Tempe, AZ 85251, USA., Promislow D; Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA 02111, USA., Karlsson E; Genomics & Computational Biology, UMass Chan Medical School; Worcester, MA 01655, USA.; Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.; Program in Molecular Medicine, UMass Chan Medical School, Worcester, MA 01655, USA., Akey JM; Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, South Drive, Princeton University, Princeton, NJ 08544, USA.
Corporate Authors: Dog Aging Project Consortium
Source: BioRxiv : the preprint server for biology [bioRxiv] 2026 Jun 04. Date of Electronic Publication: 2026 Jun 04.
Publication Type: Journal Article; Preprint
Journal Info: Country of Publication: United States NLM ID: 101680187 Publication Model: Electronic Cited Medium: Internet ISSN: 2692-8205 (Electronic) Linking ISSN: 26928205 NLM ISO Abbreviation: bioRxiv Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2692-8205
DOI:10.64898/2026.06.03.729926