MoCHI: neural networks to fit interpretable models and quantify energies, energetic couplings, epistasis, and allostery from deep mutational scanning data

Abstract We present MoCHI, a tool to fit interpretable models using deep mutational scanning data. MoCHI infers free energy changes, as well as interaction terms (energetic couplings) for specified biophysical models, including from multimodal phenotypic data. When a user-specified model is unavaila...

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Bibliographic Details

Published in:	Genome Biology
Main Authors:	Andre J. Faure, Ben Lehner
Format:	Article
Language:	English
Published:	BMC 2024-12-01
Subjects:	Deep mutational scanning Neural networks Thermodynamic models Epistasis Allostery
Online Access:	https://doi.org/10.1186/s13059-024-03444-y