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» Learning Methods for DNA Binding in Computational Biology
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BMCBI
2007
148views more  BMCBI 2007»
14 years 9 months ago
Computation of significance scores of unweighted Gene Set Enrichment Analyses
Background: Gene Set Enrichment Analysis (GSEA) is a computational method for the statistical evaluation of sorted lists of genes or proteins. Originally GSEA was developed for in...
Andreas Keller, Christina Backes, Hans-Peter Lenho...
ICCV
2003
IEEE
15 years 11 months ago
Machine Learning and Multiscale Methods in the Identification of Bivalve Larvae
This paper describes a novel application of support vector machines and multiscale texture and color invariants to a problem in biological oceanography: the identification of 6 sp...
Sanjay Tiwari, Scott Gallager
77
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ISMB
2000
14 years 11 months ago
A Practical Algorithm for Optimal Inference of Haplotypes from Diploid Populations
The next phase of human genomics will involve largescale screens of populations for signi cant DNA polymorphisms, notably single nucleotide polymorphisms SNP's. Dense human S...
Dan Gusfield
KDD
2001
ACM
163views Data Mining» more  KDD 2001»
15 years 10 months ago
Learning to recognize brain specific proteins based on low-level features from on-line prediction servers
During the last decade, the area of bioinformatics has produced an overwhelming amount of data, with the recently published draft of the human genome being the most prominent exam...
Henrik Boström, Joakim Cöster, Lars Aske...
BMCBI
2011
14 years 1 months ago
Protein alignment algorithms with an efficient backtracking routine on multiple GPUs
Background: Pairwise sequence alignment methods are widely used in biological research. The increasing number of sequences is perceived as one of the upcoming challenges for seque...
Jacek Blazewicz, Wojciech Frohmberg, Michal Kierzy...