Identification of the subcellular localization of mycobacterial proteins using localization motifs
Tang, Sheng Nan ; Sun, Jiang Ming LU
; Xiong, Wen Wei
; Cong, Pei Sheng
and Li, Tong Hua
(2012)
In Biochimie
94(3).
p.847-853
- Abstract
Mycobacterium, the most common disease-causing genus, infects billions of people and is notoriously difficult to treat. Understanding the subcellular localization of mycobacterial proteins can provide essential clues for protein function and drug discovery. In this article, we present a novel approach that focuses on local sequence information to identify localization motifs that are generated by a merging algorithm and are selected based on a binomially distributed model. These localization motifs are employed as features for identifying the subcellular localization of mycobacterial proteins. Our approach provides more accurate results than previous methods and was tested on an independent dataset recently obtained from an experimental... (More)
Mycobacterium, the most common disease-causing genus, infects billions of people and is notoriously difficult to treat. Understanding the subcellular localization of mycobacterial proteins can provide essential clues for protein function and drug discovery. In this article, we present a novel approach that focuses on local sequence information to identify localization motifs that are generated by a merging algorithm and are selected based on a binomially distributed model. These localization motifs are employed as features for identifying the subcellular localization of mycobacterial proteins. Our approach provides more accurate results than previous methods and was tested on an independent dataset recently obtained from an experimental study to provide a first and reasonably accurate prediction of subcellular localization. Our approach can also be used for large-scale prediction of new protein entries in the UniportKB database and of protein sequences obtained experimentally. In addition, our approach identified many local motifs involved with the subcellular localization that also interact with the environment. Thus, our method may have widespread applications both in the study of the functions of mycobacterial proteins and in the search for a potential vaccine target for designing drugs.
(Less)
- author
- Tang, Sheng Nan
; Sun, Jiang Ming
LU
; Xiong, Wen Wei
; Cong, Pei Sheng
and Li, Tong Hua
- publishing date
- 2012-03
- type
- Contribution to journal
- publication status
- published
- keywords
- Localization motifs, Mycobacterial, Subcellular localization
- in
- Biochimie
- volume
- 94
- issue
- 3
- pages
- 847 - 853
- publisher
- Elsevier
- external identifiers
-
- pmid:22182488
- scopus:84857062423
- ISSN
- 0300-9084
- DOI
- 10.1016/j.biochi.2011.12.003
- language
- English
- LU publication?
- no
- id
- 8cd6a75d-c04d-46a4-9151-9c20986c8886
- date added to LUP
- 2023-04-24 16:44:18
- date last changed
- 2024-01-05 00:49:09
@article{8cd6a75d-c04d-46a4-9151-9c20986c8886,
abstract = {{<p>Mycobacterium, the most common disease-causing genus, infects billions of people and is notoriously difficult to treat. Understanding the subcellular localization of mycobacterial proteins can provide essential clues for protein function and drug discovery. In this article, we present a novel approach that focuses on local sequence information to identify localization motifs that are generated by a merging algorithm and are selected based on a binomially distributed model. These localization motifs are employed as features for identifying the subcellular localization of mycobacterial proteins. Our approach provides more accurate results than previous methods and was tested on an independent dataset recently obtained from an experimental study to provide a first and reasonably accurate prediction of subcellular localization. Our approach can also be used for large-scale prediction of new protein entries in the UniportKB database and of protein sequences obtained experimentally. In addition, our approach identified many local motifs involved with the subcellular localization that also interact with the environment. Thus, our method may have widespread applications both in the study of the functions of mycobacterial proteins and in the search for a potential vaccine target for designing drugs.</p>}},
author = {{Tang, Sheng Nan and Sun, Jiang Ming and Xiong, Wen Wei and Cong, Pei Sheng and Li, Tong Hua}},
issn = {{0300-9084}},
keywords = {{Localization motifs; Mycobacterial; Subcellular localization}},
language = {{eng}},
number = {{3}},
pages = {{847--853}},
publisher = {{Elsevier}},
series = {{Biochimie}},
title = {{Identification of the subcellular localization of mycobacterial proteins using localization motifs}},
url = {{http://dx.doi.org/10.1016/j.biochi.2011.12.003}},
doi = {{10.1016/j.biochi.2011.12.003}},
volume = {{94}},
year = {{2012}},
}