Predicting gene ontology annotations from sequence data using kernel-based machine learning algorithms

Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004

Volumn , Issue , 2004, Pages 529-530

  Ward, J J ^a   Sodhi, J S ^a   Buxton, B F ^a   Jones, D T ^a  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

AMINO ACIDS; BIOASSAY; BIOCHEMISTRY; CONFORMAL MAPPING; DATABASE SYSTEMS; GENES; LAPLACE TRANSFORMS; LEARNING ALGORITHMS; LEARNING SYSTEMS; MACROMOLECULES; METABOLISM; PROTEINS; YEAST;

AMINO ACID SEQUENCE; BIOCHEMICAL PATHWAYS; GENE ONTOLOGY (GO); SACCHAROMYCES CEREVISIAE;

GENETIC ENGINEERING;

EID: 14044266917     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (5)

1. S. S. Dwight et al. Saccharomyces Genome Database (SGD) provides secondary annotation using the Gene Ontology (GO). Nucl. Acids. Res., 30(1):69-72, 2002.
2. Gene Ontology Consortium. Creating the gene ontology resource: design and implementation. Genome Research, 11:1425-1433, 2001.
3. D. T. Jones. Protein secondary structure prediction based on position-specific scoring matrices. J. Mol. Biol., 292:196-202, 1999.
4. R. I. Kondor and J. Lafferty. Diffusion kernels on graphs and other discrete structures. In Proceedings of the ICML, 2002.
5. L. J. McGuffin and D. T. Jones. Benchmarking protein secondary structure prediction for protein fold recognition. Proteins, 52:166-175, 2003.