Recommendation of: SelNeTime: a python package inferring effective population size and selection intensity from genomic time series data. Round#4

A recommendation of: Mathieu Uhl, Paul Bunel, Miguel de Navascués, Simon Boitard, Bertrand Servin SelNeTime: a python package inferring effective population size and selection intensity from genomic time series data https://doi.org/10.1101/2024.11.06.622284

Publication Details

Journal
Peer Community In Mathematical and Computational Biology
Published
2025-10-22
DOI
https://doi.org/10.24072/pci.mcb.100406
Primary Topic
Evolution and Genetic Dynamics
Type
article
Field-Weighted Citation Impact
0.00
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article

Recommendation of: SelNeTime: a python package inferring effective population size and selection intensity from genomic time series data. Round#4

Peer Community In Mathematical and Computational Biology
Evolution and Genetic Dynamics
article

Recommendation of: SelNeTime: a python package inferring effective population size and selection intensity from genomic time series data. Round#4

article en

Abstract

A recommendation of: Mathieu Uhl, Paul Bunel, Miguel de Navascués, Simon Boitard, Bertrand Servin SelNeTime: a python package inferring effective population size and selection intensity from genomic time series data https://doi.org/10.1101/2024.11.06.622284

Peer Community In Mathematical and Computational Biology
Openalex Percentile: Top 68%
Evolution and Genetic Dynamics
DOIOpen Access PDFOpenAlex
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Recommendation of: SelNeTime: a python package inferring effective population size and selection intensity from genomic time series data. Round#4 · Peer Community In Mathematical and Computational Biology (2025) | TGRS Research Map | TGRS