Author

Adam G. Fine

University of ChicagoORCID 0000-0002-6722-2674Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Matthias SteinrückeniD· 1 shared

Activity by Year

2025-2025 · peak 1/yr

1 paper

Recent·Most cited

A novel expectation-maximization approach to infer general diploid selection from time-series genetic data

Adam G. Fine, Matthias Steinrücken

This paper introduces an expectation-maximization method to infer general diploid selection from time-series genetic data, finding evidence for selection in six genomic regions from ancient DNA samples.

PLoS Genetics · Jul 22, 2025Peer-reviewedGenetics