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cs.LG2025
Attribution assignment for deep-generative sequence models enables interpretability analysis using positive-only data
Robert Frank, Michael Widrich, Rahmad Akbar +4
Generative machine learning models offer a powerful framework for therapeutic design by efficiently exploring large spaces of biological sequences enriched for desirable properties…
q-bio.GN2025
inMOTIFin: a lightweight end-to-end simulation software for regulatory sequences
Katalin Ferenc, Lorenzo Martini, Ieva Rauluseviciute +2
The accurate development, assessment, interpretation, and benchmarking of bioinformatics frameworks for analyzing transcriptional regulatory grammars rely on controlled simulations…