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» Identifying Clusters from Positive Data
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BMCBI
2010
113views more  BMCBI 2010»
13 years 10 months ago
Statistical method on nonrandom clustering with application to somatic mutations in cancer
Background: Human cancer is caused by the accumulation of tumor-specific mutations in oncogenes and tumor suppressors that confer a selective growth advantage to cells. As a conse...
Jingjing Ye, Adam Pavlícek, Elizabeth A. Lu...
BMCBI
2006
74views more  BMCBI 2006»
13 years 10 months ago
An unsupervised classification scheme for improving predictions of prokaryotic TIS
Background: Although it is not difficult for state-of-the-art gene finders to identify coding regions in prokaryotic genomes, exact prediction of the corresponding translation ini...
Maike Tech, Peter Meinicke
PR
2006
122views more  PR 2006»
13 years 10 months ago
Fast multiscale clustering and manifold identification
We present a novel multiscale clustering algorithm inspired by algebraic multigrid techniques. Our method begins with assembling data points according to local similarities. It us...
Dan Kushnir, Meirav Galun, Achi Brandt
BMCBI
2007
144views more  BMCBI 2007»
13 years 10 months ago
Assessing the ability of sequence-based methods to provide functional insight within membrane integral proteins: a case study an
Background: Efforts to predict functional sites from globular proteins is increasingly common; however, the most successful of these methods generally require structural insight. ...
Dennis R. Livesay, Patrick D. Kidd, Sepehr Eskanda...
JMM2
2008
124views more  JMM2 2008»
13 years 10 months ago
Integrated Feature Selection and Clustering for Taxonomic Problems within Fish Species Complexes
As computer and database technologies advance rapidly, biologists all over the world can share biologically meaningful data from images of specimens and use the data to classify th...
Huimin Chen, Henry L. Bart Jr., Shuqing Huang