Multiple genomic features filtration to improve protein-protein interactions prediction

Multiple genomic features filtration to improve protein-protein interactions prediction

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Bibliographic Details
Main Author: Roslan , Rosfuzah
Format: Thesis
Published: 2010
Subjects:
QA75 Electronic computers
Computer science
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id my-utm-ep.16550
record_format uketd_dc
spelling my-utm-ep.165502017-08-13T05:50:01Z Multiple genomic features filtration to improve protein-protein interactions prediction 2010 Roslan , Rosfuzah QA75 Electronic computers. Computer science 2010 Thesis http://eprints.utm.my/id/eprint/16550/ http://libraryopac.utm.my/client/en_AU/main/search/results?qu=Multiple+genomic+features+filtration+to+improve+protein-protein+interactions+prediction&te= masters Universiti Teknologi Malaysia, Faculty of Computer Science and Information System Faculty of Computer Science and Information System
institution Universiti Teknologi Malaysia
collection UTM Institutional Repository
topic QA75 Electronic computers
Computer science
spellingShingle QA75 Electronic computers
Computer science
Roslan , Rosfuzah
Multiple genomic features filtration to improve protein-protein interactions prediction
description
format Thesis
qualification_level Master's degree
author Roslan , Rosfuzah
author_facet Roslan , Rosfuzah
author_sort Roslan , Rosfuzah
title Multiple genomic features filtration to improve protein-protein interactions prediction
title_short Multiple genomic features filtration to improve protein-protein interactions prediction
title_full Multiple genomic features filtration to improve protein-protein interactions prediction
title_fullStr Multiple genomic features filtration to improve protein-protein interactions prediction
title_full_unstemmed Multiple genomic features filtration to improve protein-protein interactions prediction
title_sort multiple genomic features filtration to improve protein-protein interactions prediction
granting_institution Universiti Teknologi Malaysia, Faculty of Computer Science and Information System
granting_department Faculty of Computer Science and Information System
publishDate 2010
_version_ 1747815070257119232

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