Virtual genetic coding and time series analysis for alternative splicing prediction in C. elegans

摘要

MotivationPrediction of alternative splicing has been traditionally based on the study of expressed sequences, helped by homology considerations and the analysis of local discriminative features. More recently, machine learning algorithms have been developed that try avoid or reduce the use of a priori information, with partial success.