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

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:
QH301 Biology
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spelling my-mmu-ep.34612012-03-30T07:01:28Z Enhancing Protein Fold Prediction Accuracy Using New Physicochemical-Based Features And Fusion Of Heterogeneous Classifiers 2010-07 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 http://shdl.mmu.edu.my/3461/ http://vlib.mmu.edu.my/diglib/login/dlusr/login.php masters University of Multimedia Research Library
institution Multimedia University
collection MMU Institutional Repository
topic QH301 Biology
spellingShingle QH301 Biology
Dehzangi, Abdollah
Enhancing Protein Fold Prediction Accuracy Using New Physicochemical-Based Features And Fusion Of Heterogeneous Classifiers
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.
format Thesis
qualification_level Master's degree
author Dehzangi, Abdollah
author_facet Dehzangi, Abdollah
author_sort Dehzangi, Abdollah
title 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_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_sort enhancing protein fold prediction accuracy using new physicochemical-based features and fusion of heterogeneous classifiers
granting_institution University of Multimedia
granting_department Research Library
publishDate 2010
_version_ 1747829503358402560

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