IsoFrog: a reversible jump Markov Chain Monte Carlo feature selection-based method for predicting isoform functions.
Journal:
Bioinformatics (Oxford, England)
PMID:
37647643
Abstract
MOTIVATION: A single gene may yield several isoforms with different functions through alternative splicing. Continuous efforts are devoted to developing machine-learning methods to predict isoform functions. However, existing methods do not consider the relevance of each feature to specific functions and ignore the noise caused by the irrelevant features. In this case, we hypothesize that constructing a feature selection framework to extract the function-relevant features might help improve the model accuracy in isoform function prediction.