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BIBM
2008
IEEE
172views Bioinformatics» more  BIBM 2008»
14 years 3 months ago
Boosting Methods for Protein Fold Recognition: An Empirical Comparison
Protein fold recognition is the prediction of protein’s tertiary structure (Fold) given the protein’s sequence without relying on sequence similarity. Using machine learning t...
Yazhene Krishnaraj, Chandan K. Reddy
BMCBI
2010
190views more  BMCBI 2010»
13 years 8 months ago
APIS: accurate prediction of hot spots in protein interfaces by combining protrusion index with solvent accessibility
Background: It is well known that most of the binding free energy of protein interaction is contributed by a few key hot spot residues. These residues are crucial for understandin...
Jun-Feng Xia, Xing-Ming Zhao, Jiangning Song, De-S...
JMLR
2008
150views more  JMLR 2008»
13 years 8 months ago
Discriminative Learning of Max-Sum Classifiers
The max-sum classifier predicts n-tuple of labels from n-tuple of observable variables by maximizing a sum of quality functions defined over neighbouring pairs of labels and obser...
Vojtech Franc, Bogdan Savchynskyy
BMCBI
2010
125views more  BMCBI 2010»
13 years 8 months ago
Large-scale prediction of protein-protein interactions from structures
Background: The prediction of protein-protein interactions is an important step toward the elucidation of protein functions and the understanding of the molecular mechanisms insid...
Martial Hue, Michael Riffle, Jean-Philippe Vert, W...
DIS
2009
Springer
14 years 3 months ago
Using Data Mining for Wine Quality Assessment
Certification and quality assessment are crucial issues within the wine industry. Currently, wine quality is mostly assessed by physicochemical (e.g alcohol levels) and sensory (e...
Paulo Cortez, Juliana Teixeira, António Cer...