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» Training Invariant Support Vector Machines
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BIBE
2007
IEEE
167views Bioinformatics» more  BIBE 2007»
13 years 11 months ago
Assessing the Performance of Macromolecular Sequence Classifiers
Machine learning approaches offer some of the most cost-effective approaches to building predictive models (e.g., classifiers) in a broad range of applications in computational bio...
Cornelia Caragea, Jivko Sinapov, Vasant Honavar, D...
BMCBI
2010
134views more  BMCBI 2010»
13 years 7 months ago
Semi-automated screening of biomedical citations for systematic reviews
Background: Systematic reviews address a specific clinical question by unbiasedly assessing and analyzing the pertinent literature. Citation screening is a time-consuming and crit...
Byron C. Wallace, Thomas A. Trikalinos, Joseph Lau...
BMCBI
2007
93views more  BMCBI 2007»
13 years 7 months ago
SVM-Fold: a tool for discriminative multi-class protein fold and superfamily recognition
Background: Predicting a protein’s structural class from its amino acid sequence is a fundamental problem in computational biology. Much recent work has focused on developing ne...
Iain Melvin, Eugene Ie, Rui Kuang, Jason Weston, W...
BMCBI
2004
140views more  BMCBI 2004»
13 years 7 months ago
What can we learn from noncoding regions of similarity between genomes?
Background: In addition to known protein-coding genes, large amounts of apparently non-coding sequence are conserved between the human and mouse genomes. It seems reasonable to as...
Thomas A. Down, Tim J. P. Hubbard
AIME
2009
Springer
13 years 8 months ago
Learning Approach to Analyze Tumour Heterogeneity in DCE-MRI Data During Anti-cancer Treatment
Abstract. The paper proposes a learning approach to support medical researchers in the context of in-vivo cancer imaging, and specifically in the analysis of Dynamic Contrast-Enhan...
Alessandro Daducci, Umberto Castellani, Marco Cris...