Title |
SCPS: a fast implementation of a spectral method for detecting protein families on a genome-wide scale
|
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Published in |
BMC Bioinformatics, March 2010
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DOI | 10.1186/1471-2105-11-120 |
Pubmed ID | |
Authors |
Tamás Nepusz, Rajkumar Sasidharan, Alberto Paccanaro |
Abstract |
An important problem in genomics is the automatic inference of groups of homologous proteins from pairwise sequence similarities. Several approaches have been proposed for this task which are "local" in the sense that they assign a protein to a cluster based only on the distances between that protein and the other proteins in the set. It was shown recently that global methods such as spectral clustering have better performance on a wide variety of datasets. However, currently available implementations of spectral clustering methods mostly consist of a few loosely coupled Matlab scripts that assume a fair amount of familiarity with Matlab programming and hence they are inaccessible for large parts of the research community. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United Kingdom | 2 | 3% |
United States | 2 | 3% |
Netherlands | 1 | 2% |
Sweden | 1 | 2% |
France | 1 | 2% |
Spain | 1 | 2% |
Brazil | 1 | 2% |
Unknown | 53 | 85% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 17 | 27% |
Student > Ph. D. Student | 12 | 19% |
Student > Master | 6 | 10% |
Student > Postgraduate | 4 | 6% |
Student > Doctoral Student | 4 | 6% |
Other | 13 | 21% |
Unknown | 6 | 10% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 27 | 44% |
Computer Science | 12 | 19% |
Biochemistry, Genetics and Molecular Biology | 8 | 13% |
Engineering | 2 | 3% |
Linguistics | 1 | 2% |
Other | 6 | 10% |
Unknown | 6 | 10% |