2024
DOI: 10.1093/molbev/msae242
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Digital Image Processing to Detect Adaptive Evolution

Md Ruhul Amin,
Mahmudul Hasan,
Michael DeGiorgio

Abstract: In recent years, advances in image processing and machine learning have fueled a paradigm shift in detecting genomic regions under natural selection. Early machine learning techniques employed population-genetic summary statistics as features, which focus on specific genomic patterns expected by adaptive and neutral processes. Though such engineered features are important when training data is limited, the ease at which simulated data can now be generated has led to the recent development of approaches that ta… Show more

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