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» Predicting the beta-helix fold from protein sequence data
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ACL
2006
13 years 9 months ago
Semi-Supervised Conditional Random Fields for Improved Sequence Segmentation and Labeling
We present a new semi-supervised training procedure for conditional random fields (CRFs) that can be used to train sequence segmentors and labelers from a combination of labeled a...
Feng Jiao, Shaojun Wang, Chi-Hoon Lee, Russell Gre...
BMCBI
2004
93views more  BMCBI 2004»
13 years 7 months ago
Predicting binding sites of hydrolase-inhibitor complexes by combining several methods
Background: Protein-protein interactions play a critical role in protein function. Completion of many genomes is being followed rapidly by major efforts to identify interacting pr...
Taner Z. Sen, Andrzej Kloczkowski, Robert L. Jerni...
BMCBI
2007
127views more  BMCBI 2007»
13 years 7 months ago
Predicting the phenotypic effects of non-synonymous single nucleotide polymorphisms based on support vector machines
Background: Human genetic variations primarily result from single nucleotide polymorphisms (SNPs) that occur approximately every 1000 bases in the overall human population. The no...
Jian Tian, Ningfeng Wu, Xuexia Guo, Jun Guo, Juhua...
CORR
2006
Springer
118views Education» more  CORR 2006»
13 years 7 months ago
Integration and mining of malaria molecular, functional and pharmacological data: how far are we from a chemogenomic knowledge s
The organization and mining of malaria genomic and post-genomic data is important to significantly increase the knowledge of the biology of its causative agents, and is motivated,...
L.-M. Birkholtz, Olivier Bastien, G. Wells, D. Gra...
BMCBI
2008
123views more  BMCBI 2008»
13 years 7 months ago
Validation of protein models by a neural network approach
Background: The development and improvement of reliable computational methods designed to evaluate the quality of protein models is relevant in the context of protein structure re...
Paolo Mereghetti, Maria Luisa Ganadu, Elena Papale...