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» Predicting Nucleolar Proteins Using Support-Vector Machines
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TCBB
2008
138views more  TCBB 2008»
13 years 7 months ago
PairProSVM: Protein Subcellular Localization Based on Local Pairwise Profile Alignment and SVM
The subcellular locations of proteins are important functional annotations. An effective and reliable subcellular localization method is necessary for proteomics research. This pap...
Man-Wai Mak, Jian Guo, Sun-Yuan Kung
BMCBI
2008
153views more  BMCBI 2008»
13 years 7 months ago
Improved general regression network for protein domain boundary prediction
Background: Protein domains present some of the most useful information that can be used to understand protein structure and functions. Recent research on protein domain boundary ...
Paul D. Yoo, Abdur R. Sikder, Bing Bing Zhou, Albe...
BMCBI
2005
117views more  BMCBI 2005»
13 years 7 months ago
An SVM-based system for predicting protein subnuclear localizations
Background: The large gap between the number of protein sequences in databases and the number of functionally characterized proteins calls for the development of a fast computatio...
Zhengdeng Lei, Yang Dai
BMCBI
2007
96views more  BMCBI 2007»
13 years 7 months ago
Protein subcellular localization prediction based on compartment-specific features and structure conservation
Motivation: Protein subcellular localization is crucial for genome annotation, protein function prediction, and drug discovery. However, since determining subcellular localization...
Emily Chia-Yu Su, Hua-Sheng Chiu, Allan Lo, Jenn-K...
PR
2006
110views more  PR 2006»
13 years 7 months ago
Classifying protein sequences using hydropathy blocks
The annotation of proteins can be achieved by classifying the protein of interest into a certain known protein family to induce its functional and structural features. This paper ...
De-Shuang Huang, Xing-Ming Zhao, Guang-Bin Huang, ...