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NIPS
1998
13 years 9 months ago
Semi-Supervised Support Vector Machines
We introduce a semi-supervised support vector machine (S3 VM) method. Given a training set of labeled data and a working set of unlabeled data, S3 VM constructs a support vector m...
Kristin P. Bennett, Ayhan Demiriz
BIODATAMINING
2008
130views more  BIODATAMINING 2008»
13 years 8 months ago
Uncovering mechanisms of transcriptional regulations by systematic mining of cis regulatory elements with gene expression profil
Background: Contrary to the traditional biology approach, where the expression patterns of a handful of genes are studied at a time, microarray experiments enable biologists to st...
Qicheng Ma, Gung-Wei Chirn, Joseph D. Szustakowski...
BMCBI
2010
115views more  BMCBI 2010»
13 years 8 months ago
Integration of multiple data sources to prioritize candidate genes using discounted rating system
Background: Identifying disease gene from a list of candidate genes is an important task in bioinformatics. The main strategy is to prioritize candidate genes based on their simil...
Yongjin Li, Jagdish Chandra Patra
BMCBI
2010
104views more  BMCBI 2010»
13 years 8 months ago
Bidirectional best hit r-window gene clusters
Background: Conserved gene clusters are groups of genes that are located close to one another in the genomes of several species. They tend to code for proteins that have a functio...
Melvin Zhang, Hon Wai Leong
BMCBI
2007
166views more  BMCBI 2007»
13 years 8 months ago
Optimization of filtering criterion for SEQUEST database searching to improve proteome coverage in shotgun proteomics
Background: In proteomic analysis, MS/MS spectra acquired by mass spectrometer are assigned to peptides by database searching algorithms such as SEQUEST. The assignations of pepti...
Xinning Jiang, Xiaogang Jiang, Guanghui Han, Mingl...