Literature DB >> 14990457

Support vector machine classification on the web.

Paul Pavlidis1, Ilan Wapinski, William Stafford Noble.   

Abstract

The support vector machine (SVM) learning algorithm has been widely applied in bioinformatics. We have developed a simple web interface to our implementation of the SVM algorithm, called Gist. This interface allows novice or occasional users to apply a sophisticated machine learning algorithm easily to their data. More advanced users can download the software and source code for local installation. The availability of these tools will permit more widespread application of this powerful learning algorithm in bioinformatics.

Mesh:

Year:  2004        PMID: 14990457     DOI: 10.1093/bioinformatics/btg461

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  34 in total

1.  EHPred: an SVM-based method for epoxide hydrolases recognition and classification.

Authors:  Jia Jia; Liang Yang; Zi-Zhang Zhang
Journal:  J Zhejiang Univ Sci B       Date:  2006-01       Impact factor: 3.066

2.  RNA secondary structure mediates alternative 3'ss selection in Saccharomyces cerevisiae.

Authors:  Mireya Plass; Carles Codony-Servat; Pedro Gabriel Ferreira; Josep Vilardell; Eduardo Eyras
Journal:  RNA       Date:  2012-04-26       Impact factor: 4.942

3.  Effects of SVM parameter optimization on discrimination and calibration for post-procedural PCI mortality.

Authors:  Michael E Matheny; Frederic S Resnic; Nipun Arora; Lucila Ohno-Machado
Journal:  J Biomed Inform       Date:  2007-05-18       Impact factor: 6.317

4.  Global survey of escape from X inactivation by RNA-sequencing in mouse.

Authors:  Fan Yang; Tomas Babak; Jay Shendure; Christine M Disteche
Journal:  Genome Res       Date:  2010-04-02       Impact factor: 9.043

5.  Data mining approaches for genome-wide association of mood disorders.

Authors:  Mehdi Pirooznia; Fayaz Seifuddin; Jennifer Judy; Pamela B Mahon; James B Potash; Peter P Zandi
Journal:  Psychiatr Genet       Date:  2012-04       Impact factor: 2.458

6.  Extensive and varied modifications in histone H2B of wild-type and histone deacetylase 1 mutant Neurospora crassa.

Authors:  D C Anderson; George R Green; Kristina Smith; Eric U Selker
Journal:  Biochemistry       Date:  2010-06-29       Impact factor: 3.162

7.  Cell cycle kinases predicted from conserved biophysical properties.

Authors:  Kazimierz O Wrzeszczynski; Burkhard Rost
Journal:  Proteins       Date:  2009-02-15

8.  Characterizing nucleosome dynamics from genomic and epigenetic information using rule induction learning.

Authors:  Ngoc Tu Le; Tu Bao Ho; Dang Hung Tran
Journal:  BMC Genomics       Date:  2009-12-03       Impact factor: 3.969

9.  Proteome-wide prediction of novel DNA/RNA-binding proteins using amino acid composition and periodicity in the hyperthermophilic archaeon Pyrococcus furiosus.

Authors:  Kosuke Fujishima; Mizuki Komasa; Sayaka Kitamura; Haruo Suzuki; Masaru Tomita; Akio Kanai
Journal:  DNA Res       Date:  2007-06-15       Impact factor: 4.458

10.  LipocalinPred: a SVM-based method for prediction of lipocalins.

Authors:  Jayashree Ramana; Dinesh Gupta
Journal:  BMC Bioinformatics       Date:  2009-12-24       Impact factor: 3.169

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