Are grammatical representations useful for learning from biological sequence data? - A case study

Journal of Computational Biology

Volumn 8, Issue 5, 2001, Pages 493-521

  Muggleton, S H ^a   Bryant, C H ^a   Srinivasan, A ^b   Whittaker, A ^c   Topp, S ^c   Rawlings, C ^c  

^a UNIVERSITY OF YORK   (United Kingdom)

^b UNIVERSITY OF OXFORD   (United Kingdom)

^c GLAXOSMITHKLINE   (United Kingdom)

Author keywords

Bioinformatics; Cost function; Grammatical inference; Inductive logic programming; Machine learning

Indexed keywords

AMALGAM; NEUROPEPTIDE;

ACCURACY; AMINO ACID SEQUENCE; ANALYTIC METHOD; ARTICLE; CASE STUDY; COST EFFECTIVENESS ANALYSIS; ENZYME ACTIVITY; HUMAN; INFORMATION SCIENCE; LEARNING; MOLECULAR GENETICS; PERFORMANCE; PRECURSOR; PREDICTION; PRIORITY JOURNAL; PROTEIN SYNTHESIS; RECOGNITION;

BAYES THEOREM; COMPUTATIONAL BIOLOGY; HUMANS; NEUROPEPTIDES; PROTEIN PRECURSORS; SEQUENCE ANALYSIS; SOFTWARE DESIGN;

EID: 0034762306     PISSN: 10665277     EISSN: None     Source Type: Journal    
DOI: 10.1089/106652701753216512     Document Type: Article

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