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Article

Uncovering Epistatic Interactions in SARS-CoV-2 Evolution Through Hidden Markov Models.

Journal of computational biology : a journal of computational molecular cell biology - 1 Jan 2026

Adeniyi Ayotomiwa Ezekiel, Juyal Akshay, Skums Pavel, Patterson Murray, Zelikovsky Alex

Abstract excerpt

Understanding epistatic interactions, where mutations collectively influence viral fitness, is critical for predicting pathogen evolution. We present a hidden Markov model (HMM) framework that captures the temporal dynamics of epistatic relationships in SARS-CoV-2, addressing limitations of static network-based approaches. Our method models single amino acid variant pairs as a two-state system (linked/unlinked),...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Identifiers

PMID: 41719088
DOI: 10.1177/15578666261423963

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 5 Sept 2026.

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