Enhancing Protein Fold Prediction Accuracy Using New Physicochemical-Based Features And Fusion Of Heterogeneous Classifiers

One of the most challenging research areas in the bioinformatics is to predict the tertiary structure of a protein from its amino sequence. Difficulties of this task, such lack of knowledge about the protein structural stability or how the amino acids interact with each other along the amino acid se...

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Main Author: Dehzangi, Abdollah
Format: Thesis
Published: 2010
Subjects:
Online Access:http://shdl.mmu.edu.my/3461/
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author Dehzangi, Abdollah
author_facet Dehzangi, Abdollah
author_sort Dehzangi, Abdollah
building MMU Institutional Repository
collection Online Access
description One of the most challenging research areas in the bioinformatics is to predict the tertiary structure of a protein from its amino sequence. Difficulties of this task, such lack of knowledge about the protein structural stability or how the amino acids interact with each other along the amino acid sequence of a protein have made this an open search issue for the bioinformatics and the molecular biology.
first_indexed 2025-11-14T18:10:57Z
format Thesis
id mmu-3461
institution Multimedia University
institution_category Local University
last_indexed 2025-11-14T18:10:57Z
publishDate 2010
recordtype eprints
repository_type Digital Repository
spelling mmu-34612012-03-30T07:01:28Z http://shdl.mmu.edu.my/3461/ Enhancing Protein Fold Prediction Accuracy Using New Physicochemical-Based Features And Fusion Of Heterogeneous Classifiers Dehzangi, Abdollah QH301 Biology One of the most challenging research areas in the bioinformatics is to predict the tertiary structure of a protein from its amino sequence. Difficulties of this task, such lack of knowledge about the protein structural stability or how the amino acids interact with each other along the amino acid sequence of a protein have made this an open search issue for the bioinformatics and the molecular biology. 2010-07 Thesis NonPeerReviewed Dehzangi, Abdollah (2010) Enhancing Protein Fold Prediction Accuracy Using New Physicochemical-Based Features And Fusion Of Heterogeneous Classifiers. Masters thesis, University of Multimedia. http://vlib.mmu.edu.my/diglib/login/dlusr/login.php
spellingShingle QH301 Biology
Dehzangi, Abdollah
Enhancing Protein Fold Prediction Accuracy Using New Physicochemical-Based Features And Fusion Of Heterogeneous Classifiers
title Enhancing Protein Fold Prediction Accuracy Using New Physicochemical-Based Features And Fusion Of Heterogeneous Classifiers
title_full Enhancing Protein Fold Prediction Accuracy Using New Physicochemical-Based Features And Fusion Of Heterogeneous Classifiers
title_fullStr Enhancing Protein Fold Prediction Accuracy Using New Physicochemical-Based Features And Fusion Of Heterogeneous Classifiers
title_full_unstemmed Enhancing Protein Fold Prediction Accuracy Using New Physicochemical-Based Features And Fusion Of Heterogeneous Classifiers
title_short Enhancing Protein Fold Prediction Accuracy Using New Physicochemical-Based Features And Fusion Of Heterogeneous Classifiers
title_sort enhancing protein fold prediction accuracy using new physicochemical-based features and fusion of heterogeneous classifiers
topic QH301 Biology
url http://shdl.mmu.edu.my/3461/
http://shdl.mmu.edu.my/3461/