Detecting and quantifying networks of biological kinship via exponential family random graph models.

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Title: Detecting and quantifying networks of biological kinship via exponential family random graph models.
Authors: Rohrlach AB; Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, Leipzig 04103, Germany.; School of Biological Sciences, University of Adelaide, North Terrace campus, Adelaide 5005, Australia., Gnecchi-Ruscone GA; Archaeo- and Palaeogenetics, Institute for Archaeological Sciences, Department of Geosciences, University of Tübingen, Geschwister-Scholl-Platz, Tübingen 72074, Germany.; Senckenberg Centre for Human Evolution and Palaeoenvironment at the University of Tübingen, Geschwister-Scholl-Platz, Tübingen 72074, Germany., Hofmanová Z; Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, Leipzig 04103, Germany.; Department of Archaeology and Museology, Masaryk University, Žerotínovo nám. 617/9, Brno 601 77, Czechia., Rácz Z; Institute of Archaeological Sciences, ELTE - Eötvös Loránd University, Múzeum krt. 4/B, Budapest 1088, Hungary., Roughan M; School of Mathematical and Computer Sciences, University of Adelaide, North Terrace campus, Adelaide 5005, Australia., Haak W; Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, Leipzig 04103, Germany., Tuke J; School of Mathematical and Computer Sciences, University of Adelaide, North Terrace campus, Adelaide 5005, Australia.
Source: Genetics [Genetics] 2026 Apr 04; Vol. 232 (4).
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Oxford University Press Country of Publication: United States NLM ID: 0374636 Publication Model: Print Cited Medium: Internet ISSN: 1943-2631 (Electronic) Linking ISSN: 00166731 NLM ISO Abbreviation: Genetics Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1943-2631
DOI:10.1093/genetics/iyag053