From sequences to therapeutics: Using machine learning to predict chemically modified siRNA activity

This study presents the first application of ML to efficiently classify chemically modified siRNAs on the basis of sequence and chemical modification patterns alone. Three algorithms were evaluated at three classification thresholds and compared according to sensitivity, specificity, consistency of feature weights with empirical knowledge, and performance using an external validation dataset. Finally, possible directions for future research were proposed.PMID:38431033 | DOI:10.1016/j.ygeno.2024.110815
Source: Genomics - Category: Genetics & Stem Cells Authors: Source Type: research