Automatic structure classification of small proteins using random forest

Background: Random forest, an ensemble based supervised machine learning algorithm, is used to predict the SCOP structural classification for a target structure, based on the similarity of its structural descriptors to those of a template structure with an equal number of secondary structure elements (SSEs). An initial assessment of random forest is carried out for domains consisting of three SSEs. The usability of random forest in classifying larger domains is demonstrated by applying it to domains consisting of four, five and six SSEs.

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Pooja Jain, Jonathan D. Hirst
• Keywords: BMCBI 2010, Random Forest, SCOP Structural Classification, Target Structure