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Protein Folding Optimization in a Hydrophobic-Polar Model for Predicting Tertiary Structure Using Fruit Fly Optimization Algorithm

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dc.contributor.advisor Shill, Prof. Dr. Pintu Chandra
dc.contributor.author Chatterjee, Sajib
dc.date.accessioned 2020-11-11T04:34:50Z
dc.date.available 2020-11-11T04:34:50Z
dc.date.copyright 2020
dc.date.issued 2020-02
dc.identifier.other ID 1707554
dc.identifier.uri http://hdl.handle.net/20.500.12228/897
dc.description This thesis is submitted to the Department of Computer Science and Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, February 2020. en_US
dc.description Cataloged from PDF Version of Thesis.
dc.description Includes bibliographical references (pages 59-64).
dc.description.abstract The prediction of the three-dimensional structure of a protein from its amino acid sequence is an experiment that is very much well known optimization problem which is known as the Protein Folding Optimization (PFO) in many years. The PFO problem states to the computational problem of how to predict the local structure of a protein from its amino acid. PFO problem is the NP-hard and most challenging problem. Various kind of optimization algorithm already applied for solving the PFO problem, but none of the existing algorithm not provide the accurate result within optimal time. Fruit Fly Optimization Algorithm (FOA) is a recent metaheuristics algorithm that have the intensity and diversity characteristics of searching technique. Therefore, we applied FOA for solving PFO problem in the HP (Hydrophobic-Polar) cubic lattice model. In order to increase the convergence of the FOA, we have designed and developed three different operators of FOA: smell-based search, local vision-based search and global vision-based search technique for the perspective of PFO problem. The proposed algorithm is based on two extra mechanisms centroid hydrophobic and moderator mechanism, which are accountable for improving the accomplishment of the algorithm. The centroid hydrophobic mechanism tries to move the hydrophobic monomers to the center position of the structure. The moderator mechanisms try to move a part of monomers in the protein sequence each possible directions and place at the position where the maximum energy value found. This two extra mechanisms improved the performance of the propose algorithm magically. Moreover, we have developed a reconstruction operator for producing an accurate 3D structure of protein sequences by erasing overlapping in cubic lattice points. The experiment result shows of our proposed Fruit Fly Optimization Algorithm for Protein Folding Optimization (PFO_FOA) provide better accuracy than the existing algorithms. en_US
dc.description.statementofresponsibility Sajib Chatterjee
dc.format.extent 65 pages
dc.language.iso en_US en_US
dc.publisher Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh en_US
dc.rights Khulna University of Engineering & Technology (KUET) thesis/dissertation/internship reports are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subject Protein en_US
dc.subject Amino Acid en_US
dc.subject Protein Folding Optimization (PFO) en_US
dc.subject Fruit Fly Optimization Algorithm (FOA) en_US
dc.title Protein Folding Optimization in a Hydrophobic-Polar Model for Predicting Tertiary Structure Using Fruit Fly Optimization Algorithm en_US
dc.type Thesis en_US
dc.description.degree Master of Science in Computer Science and Engineering
dc.contributor.department Department of Computer Science and Engineering


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