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KDD
2004
ACM
166views Data Mining» more  KDD 2004»
14 years 8 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
BMCBI
2006
102views more  BMCBI 2006»
13 years 7 months ago
UVPAR: fast detection of functional shifts in duplicate genes
Background: The imprint of natural selection on gene sequences is often difficult to detect. A plethora of methods have been devised to detect genetic changes due to selective pro...
Vicente Arnau, Miguel Gallach, J. Ignasi Lucas, Ig...
BMCBI
2005
160views more  BMCBI 2005»
13 years 7 months ago
Data-poor categorization and passage retrieval for Gene Ontology Annotation in Swiss-Prot
Background: In the context of the BioCreative competition, where training data were very sparse, we investigated two complementary tasks: 1) given a Swiss-Prot triplet, containing...
Frédéric Ehrler, Antoine Geissbü...
BMCBI
2007
97views more  BMCBI 2007»
13 years 7 months ago
Relating destabilizing regions to known functional sites in proteins
Background: Most methods for predicting functional sites in protein 3D structures, rely on information on related proteins and cannot be applied to proteins with no known relative...
Benoit H. Dessailly, Marc F. Lensink, Shoshana J. ...
BMCBI
2008
95views more  BMCBI 2008»
13 years 7 months ago
Mining protein networks for synthetic genetic interactions
Background: The local connectivity and global position of a protein in a protein interaction network are known to correlate with some of its functional properties, including its e...
Sri R. Paladugu, Shan Zhao, Animesh Ray, Alpan Rav...