Protein secondary sturcture prediction using artifical neural networks and support vectors machines

Protein secondary sturcture prediction using artifical neural networks and support vectors machines

In this thesis, a novel Hybrid Neural Networks Predictor (HNNP) system for the Protein Secondary Structure Prediction (PSSP) problem is described. By explor- ing such a new hybrid system, the intention is to investigate the feasibility of the HNNP in PSSP and even achieve improvements over existing...

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Bibliographic Details
Main Author: Jin, Guosheng
Other Authors: Wang Lipo
Format: Theses and Dissertations
Published: 2008
Subjects:
DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
DRNTU::Engineering::Computer science and engineering::Computing methodologies
Online Access:https://hdl.handle.net/10356/4454
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Institution: Nanyang Technological University
Description
Summary:In this thesis, a novel Hybrid Neural Networks Predictor (HNNP) system for the Protein Secondary Structure Prediction (PSSP) problem is described. By explor- ing such a new hybrid system, the intention is to investigate the feasibility of the HNNP in PSSP and even achieve improvements over existing methods. The proposed system is a cascaded network of the Radial Basis Function Neural Net- work (RBFNN) and the Multi-Layer Perceptron Neural Network (MLPNN).

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