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» Predicting Nucleolar Proteins Using Support-Vector Machines
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BMCBI
2010
120views more  BMCBI 2010»
13 years 7 months ago
KiDoQ: using docking based energy scores to develop ligand based model for predicting antibacterials
Background: Identification of novel drug targets and their inhibitors is a major challenge in the field of drug designing and development. Diaminopimelic acid (DAP) pathway is a u...
Aarti Garg, Rupinder Tewari, Gajendra P. S. Raghav...
BMCBI
2007
116views more  BMCBI 2007»
13 years 7 months ago
Clustering protein environments for function prediction: finding PROSITE motifs in 3D
Background: Structural genomics initiatives are producing increasing numbers of threedimensional (3D) structures for which there is little functional information. Structure-based ...
Sungroh Yoon, Jessica C. Ebert, Eui-Young Chung, G...
NIPS
2007
13 years 8 months ago
A Risk Minimization Principle for a Class of Parzen Estimators
This paper1 explores the use of a Maximal Average Margin (MAM) optimality principle for the design of learning algorithms. It is shown that the application of this risk minimizati...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...
BMCBI
2010
127views more  BMCBI 2010»
13 years 7 months ago
Computational prediction of type III secreted proteins from gram-negative bacteria
Background: Type III secretion system (T3SS) is a specialized protein delivery system in gramnegative bacteria that injects proteins (called effectors) directly into the eukaryoti...
Yang Yang, Jiayuan Zhao, Robyn L. Morgan, Wenbo Ma...
BMCBI
2005
134views more  BMCBI 2005»
13 years 7 months ago
Systematic feature evaluation for gene name recognition
In task 1A of the BioCreAtIvE evaluation, systems had to be devised that recognize words and phrases forming gene or protein names in natural language sentences. We approach this ...
Jörg Hakenberg, Steffen Bickel, Conrad Plake,...