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Oligo kernels for datamining on biological sequences: a case study on prokaryotic translation initiation sites

Meinicke, Peter and Tech, Maike and Morgenstern, Burkhard and Merkl, Rainer (2004) Oligo kernels for datamining on biological sequences: a case study on prokaryotic translation initiation sites. BMC Bioinformatics 5 (1), p. 169.

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Other URL: http://www.biomedcentral.com/1471-2105/5/169


Abstract

BACKGROUND: Kernel-based learning algorithms are among the most advanced machine learning methods and have been successfully applied to a variety of sequence classification tasks within the field of bioinformatics. Conventional kernels utilized so far do not provide an easy interpretation of the learnt representations in terms of positional and compositional variability of the underlying ...

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Item Type:Article
Date:2004
Institutions:Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Reinhard Sterner > Arbeitsgruppe PD Dr. Rainer Merkl
Identification Number:
ValueType
15511290PubMed ID
10.1186/1471-2105-5-169DOI
Classification:
NotationType
AlgorithmsMESH
Artificial IntelligenceMESH
Codon, Initiator/genetics*MESH
Computational Biology/methodsMESH
Computer GraphicsMESH
Databases, GeneticMESH
Escherichia coli K12/geneticsMESH
Genes, Bacterial/geneticsMESH
Models, Genetic*MESH
Prokaryotic Initiation Factors/genetics*MESH
Sequence Alignment/methodsMESH
Subjects:500 Science > 570 Life sciences
Status:Published
Refereed:Yes, this version has been refereed
Created at the University of Regensburg:Partially
Owner: Rainer Merkl
Deposited On:16 Nov 2009 10:13
Last Modified:13 Mar 2014 12:05
Item ID:10919
Owner Only: item control page

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