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» Active machine learning for transmembrane helix prediction
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BMCBI
2010
125views more  BMCBI 2010»
13 years 6 months ago
Active machine learning for transmembrane helix prediction
Background: About 30% of genes code for membrane proteins, which are involved in a wide variety of crucial biological functions. Despite their importance, experimentally determine...
Hatice U. Osmanbeyoglu, Jessica A. Wehner, Jaime G...
ISMIS
2005
Springer
13 years 11 months ago
A Machine Text-Inspired Machine Learning Approach for Identification of Transmembrane Helix Boundaries
In this paper, we adapt a statistical learning approach, inspired by automated topic segmentation techniques in speech-recognized documents to the challenging protein segmentation ...
Betty Yee Man Cheng, Jaime G. Carbonell, Judith Kl...
BMCBI
2008
147views more  BMCBI 2008»
13 years 6 months ago
Transmembrane helix prediction using amino acid property features and latent semantic analysis
Background: Prediction of transmembrane (TM) helices by statistical methods suffers from lack of sufficient training data. Current best methods use hundreds or even thousands of f...
Madhavi Ganapathiraju, Narayanas Balakrishnan, Raj...
ISMB
1993
13 years 7 months ago
Transmembrane Segment Prediction from Protein Sequence Data
Weconsider tile automatedidentification of transmembrane domains in membrane protein sequences. 324 proteins (containing 1585 segrrmnts) werc examined, representing every protein ...
Sholom M. Weiss, Dawn M. Cohen, Nitin Indurkhya
ESWA
2006
122views more  ESWA 2006»
13 years 6 months ago
Transmembrane segments prediction and understanding using support vector machine and decision tree
In recent years, there have been many studies focusing on improving the accuracy of prediction of transmembrane segments, and many significant results have been achieved. In spite...
Jieyue He, Hae-Jin Hu, Robert W. Harrison, Phang C...