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» Reformulating Constraint Models Using Input Data
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BMCBI
2006
119views more  BMCBI 2006»
15 years 2 months ago
Hidden Markov Model Variants and their Application
Markov statistical methods may make it possible to develop an unsupervised learning process that can automatically identify genomic structure in prokaryotes in a comprehensive way...
Stephen Winters-Hilt
126
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BMCBI
2008
128views more  BMCBI 2008»
15 years 2 months ago
SIGffRid: A tool to search for sigma factor binding sites in bacterial genomes using comparative approach and biologically drive
Background: Many programs have been developed to identify transcription factor binding sites. However, most of them are not able to infer two-word motifs with variable spacer leng...
Fabrice Touzain, Sophie Schbath, Isabelle Debled-R...
IJCV
2008
266views more  IJCV 2008»
15 years 2 months ago
Learning to Recognize Objects with Little Supervision
This paper shows (i) improvements over state-of-the-art local feature recognition systems, (ii) how to formulate principled models for automatic local feature selection in object c...
Peter Carbonetto, Gyuri Dorkó, Cordelia Sch...
115
Voted
BMCBI
2006
131views more  BMCBI 2006»
15 years 2 months ago
The statistics of identifying differentially expressed genes in Expresso and TM4: a comparison
Background: Analysis of DNA microarray data takes as input spot intensity measurements from scanner software and returns differential expression of genes between two conditions, t...
Allan A. Sioson, Shrinivasrao P. Mane, Pinghua Li,...
133
Voted
ACSC
2007
IEEE
15 years 6 months ago
Cross-Layer Verification of Type Flaw Attacks on Security Protocols
Security protocols are often specified at the application layer; however, application layer specifications give little detail regarding message data structures at the presentation...
Benjamin W. Long, Colin J. Fidge, David A. Carring...