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BMCBI
2006
121views more  BMCBI 2006»
15 years 7 months ago
Splice site identification using probabilistic parameters and SVM classification
Background: Recent advances and automation in DNA sequencing technology has created a vast amount of DNA sequence data. This increasing growth of sequence data demands better and ...
A. K. M. A. Baten, Bill C. H. Chang, Saman K. Halg...
BMCBI
2006
137views more  BMCBI 2006»
15 years 7 months ago
A maximum likelihood framework for protein design
Background: The aim of protein design is to predict amino-acid sequences compatible with a given target structure. Traditionally envisioned as a purely thermodynamic question, thi...
Claudia L. Kleinman, Nicolas Rodrigue, Céci...
JMLR
2008
230views more  JMLR 2008»
15 years 7 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
JCB
2006
129views more  JCB 2006»
15 years 7 months ago
GenRate: A Generative Model that Reveals Novel Transcripts in Genome-Tiling Microarray Data
Genome-wide microarray designs containing millions to hundreds of millions of probes are available for a variety of mammals, including mouse and human. These genome tiling arrays ...
Brendan J. Frey, Quaid Morris, Timothy R. Hughes
BMCBI
2004
96views more  BMCBI 2004»
15 years 7 months ago
Gene finding in novel genomes
Background: Computational gene prediction continues to be an important problem, especially for genomes with little experimental data. Results: I introduce the SNAP gene finder whi...
Ian Korf