Searching for interpretable rules for disease mutations: a simulated annealing bump hunting strategy

Background: Understanding how amino acid substitutions affect protein functions is critical for the study of proteins and their implications in diseases. Although methods have been developed for predicting potential effects of amino acid substitutions using sequence, three-dimensional structural, and evolutionary properties of proteins, the applications are limited by the complication of the features and the availability of protein structural information. Another limitation is that the prediction results are hard to be interpreted with physicochemical principles and biological knowledge. Results: To overcome these limitations, we proposed a novel feature set using physicochemical properties of amino acids, evolutionary profiles of proteins, and protein sequence information. We applied the support vector machine and the random forest with the feature set to experimental amino acid substitutions occurring in the E. coli lac repressor and the bacteriophage T4 lysozyme, as well as to anno...

• Type: Journal
• Year: 2006
• Where: BMCBI
• Authors: Rui Jiang, Hua Yang, Fengzhu Sun, Ting Chen
• Keywords: Amino Acid Substitutions, BMCBI 2006, Proteins, Support Vector Machine