PMut2: a web-based tool for predicting pathological mutations on proteins
Tipus de documentText en actes de congrés
Data publicació2015-05-05
EditorBarcelona Supercomputing Center
Condicions d'accésAccés obert
Llevat que s'hi indiqui el contrari, els
continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
:
Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
Abstract
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.
CitacióLópez-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.
Fitxers | Descripció | Mida | Format | Visualitza |
---|---|---|---|---|
127-129 PMut2 a ... oral Symposium 2016-32.pdf | 894,9Kb | Visualitza/Obre |