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» A machine learning approach for the identification of odoran...
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BMCBI
2007
91views more  BMCBI 2007»
13 years 7 months ago
A machine learning approach for the identification of odorant binding proteins from sequence-derived properties
Background: Odorant binding proteins (OBPs) are believed to shuttle odorants from the environment to the underlying odorant receptors, for which they could potentially serve as od...
Ganesan Pugalenthi, E. Ke Tang, Ponnuthurai N. Sug...
BMCBI
2007
126views more  BMCBI 2007»
13 years 7 months ago
High-throughput identification of interacting protein-protein binding sites
Background: With the advent of increasing sequence and structural data, a number of methods have been proposed to locate putative protein binding sites from protein surfaces. Ther...
Jo-Lan Chung, Wei Wang, Philip E. Bourne
BMCBI
2007
121views more  BMCBI 2007»
13 years 7 months ago
Predicting zinc binding at the proteome level
Background: Metalloproteins are proteins capable of binding one or more metal ions, which may be required for their biological function, for regulation of their activities or for ...
Andrea Passerini, Claudia Andreini, Sauro Menchett...
BMCBI
2005
125views more  BMCBI 2005»
13 years 7 months ago
A simple approach for protein name identification: prospects and limits
Background: Significant parts of biological knowledge are available only as unstructured text in articles of biomedical journals. By automatically identifying gene and gene produc...
Katrin Fundel, Daniel Güttler, Ralf Zimmer, J...
BMCBI
2008
173views more  BMCBI 2008»
13 years 7 months ago
Improved machine learning method for analysis of gas phase chemistry of peptides
Background: Accurate peptide identification is important to high-throughput proteomics analyses that use mass spectrometry. Search programs compare fragmentation spectra (MS/MS) o...
Allison Gehrke, Shaojun Sun, Lukasz A. Kurgan, Nat...