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» Sequence kernels for predicting protein essentiality
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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
2010
189views more  BMCBI 2010»
13 years 7 months ago
High quality protein sequence alignment by combining structural profile prediction and profile alignment using SABERTOOTH
Background: Protein alignments are an essential tool for many bioinformatics analyses. While sequence alignments are accurate for proteins of high sequence similarity, they become...
Florian Teichert, Jonas Minning, Ugo Bastolla, Mar...
IPPS
2008
IEEE
14 years 1 months ago
Adaptive Locality-Effective Kernel Machine for protein phosphorylation site prediction
In this study, we propose a new machine learning model namely, Adaptive Locality-Effective Kernel Machine (Adaptive-LEKM) for protein phosphorylation site prediction. Adaptive-LEK...
Paul D. Yoo, Yung Shwen Ho, Bing Bing Zhou, Albert...
BIBM
2008
IEEE
125views Bioinformatics» more  BIBM 2008»
13 years 9 months ago
On the Role of Local Matching for Efficient Semi-supervised Protein Sequence Classification
Recent studies in protein sequence analysis have leveraged the power of unlabeled data. For example, the profile and mismatch neighborhood kernels have shown significant improveme...
Pavel P. Kuksa, Pai-Hsi Huang, Vladimir Pavlovic
EVOW
2006
Springer
13 years 11 months ago
Human Papillomavirus Risk Type Classification from Protein Sequences Using Support Vector Machines
Infection by the human papillomavirus (HPV) is associated with the development of cervical cancer. HPV can be classified to highand low-risk type according to its malignant potenti...
Sun Kim, Byoung-Tak Zhang