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BMCBI
2010
179views more  BMCBI 2010»
13 years 7 months ago
A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties
Background: Genetic interaction profiles are highly informative and helpful for understanding the functional linkages between genes, and therefore have been extensively exploited ...
Zhuhong You, Zheng Yin, Kyungsook Han, De-Shuang H...
CEC
2010
IEEE
13 years 8 months ago
Evolutionary layered hypernetworks for identifying microRNA-mRNA regulatory modules
Abstract-- Exploring microRNA (miRNA) and mRNA regulatory interactions may give new insights into diverse biological phenomena. While elucidating complex miRNA-mRNA interactions ha...
Soo-Jin Kim, JungWoo Ha, Bado Lee, Byoung-Tak Zhan...
NIPS
2003
13 years 9 months ago
Max-Margin Markov Networks
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
Benjamin Taskar, Carlos Guestrin, Daphne Koller
BMCBI
2008
118views more  BMCBI 2008»
13 years 7 months ago
Virtual screening of GPCRs: An in silico chemogenomics approach
The G-protein coupled receptor (GPCR) superfamily is currently the largest class of therapeutic targets. In silico prediction of interactions between GPCRs and small molecules is ...
Laurent Jacob, Brice Hoffmann, Véronique St...
BMCBI
2004
176views more  BMCBI 2004»
13 years 7 months ago
Boosting accuracy of automated classification of fluorescence microscope images for location proteomics
Background: Detailed knowledge of the subcellular location of each expressed protein is critical to a full understanding of its function. Fluorescence microscopy, in combination w...
Kai Huang, Robert F. Murphy