PMut2: a web-based tool for predicting pathological mutations on proteins
Document typeConference report
PublisherBarcelona Supercomputing Center
Rights accessOpen Access
Amino acid substitutions in proteins can result in an altered phenotype which might lead to a disease. PMut2 is a method that can predict whether a mutation has a pathological effect on the protein function. It uses current machine learning algorithms based on protein sequence derived information. The accuracy of PMut2 is as high as 82%, with a Matthews correlation coefficient of 0,62. PMut2 predictions can be obtained through a modern website which also allows to apply the same machine learning methodology that is used to train PMut2 to custom training sets, allowing users to build their own tailor-made predictors.
CitationLópez-Ferrando, Victor [et al.]. PMut2: a web-based tool for predicting pathological mutations on proteins. A: 3rd BSC International Doctoral Symposium. "Book of abstracts". Barcelona Supercomputing Center, 2015, p. 127-129.