Protein subcellular localization prediction for lactic acid bacteria using optimal protein feature encoding scheme

Protein subcellular localization prediction for lactic acid bacteria using optimal protein feature encoding scheme

Saved in:
Bibliographic Details
Main Author: Muhamad Shukri, Nurul Akmal
Format: Thesis
Published: 2011
Subjects:
Unspecified
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-utm-ep.26124
record_format uketd_dc
spelling my-utm-ep.261242012-06-25T02:26:13Z Protein subcellular localization prediction for lactic acid bacteria using optimal protein feature encoding scheme 2011 Muhamad Shukri, Nurul Akmal Unspecified 2011 Thesis http://eprints.utm.my/id/eprint/26124/ 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 Unspecified
spellingShingle Unspecified
Muhamad Shukri, Nurul Akmal
Protein subcellular localization prediction for lactic acid bacteria using optimal protein feature encoding scheme
description
format Thesis
qualification_level Master's degree
author Muhamad Shukri, Nurul Akmal
author_facet Muhamad Shukri, Nurul Akmal
author_sort Muhamad Shukri, Nurul Akmal
title Protein subcellular localization prediction for lactic acid bacteria using optimal protein feature encoding scheme
title_short Protein subcellular localization prediction for lactic acid bacteria using optimal protein feature encoding scheme
title_full Protein subcellular localization prediction for lactic acid bacteria using optimal protein feature encoding scheme
title_fullStr Protein subcellular localization prediction for lactic acid bacteria using optimal protein feature encoding scheme
title_full_unstemmed Protein subcellular localization prediction for lactic acid bacteria using optimal protein feature encoding scheme
title_sort protein subcellular localization prediction for lactic acid bacteria using optimal protein feature encoding scheme
granting_institution Universiti Teknologi Malaysia, Faculty of Computer Science and Information System
granting_department Faculty of Computer Science and Information System
publishDate 2011
_version_ 1747815457933492224

Similar Items