Two-stage support vector machines for protein structure and solvent prediction

Two-stage support vector machines for protein structure and solvent prediction

We propose Two-Stage Support Vector Machines (TSSVM) for the prediction of structural properties of amino acid residues, namely, relative solvent accessibilities and protein secondary structure elements. The second stage of TSSVM extends the classical SVM approach to capture the contextual informati...

Full description

Saved in:
Bibliographic Details
Main Author: Nguyen, Ngoc Minh
Other Authors: Jagath C. Rajapakse
Format: Theses and Dissertations
Published: 2008
Subjects:
DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences
Online Access:https://hdl.handle.net/10356/2407
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Description
Summary:We propose Two-Stage Support Vector Machines (TSSVM) for the prediction of structural properties of amino acid residues, namely, relative solvent accessibilities and protein secondary structure elements. The second stage of TSSVM extends the classical SVM approach to capture the contextual information among the secondary structural elements or the relative solvent accessibilities and thereby improves the accuracies of the predictions.

Similar Items