Predicting functional class of M. tuberculosis and E. coli ORFs from sequence using machine learning and data mining. Original data, rules and predictions.
Data used in predicting functional class of S. cerevisiae using machine learning and data mining. Sequence, phenotype, expression, homology and predicted secondary structure data.
Data used in predicting functional class of A. thaliana using machine learning and data mining. Sequence, SCOP class, InterPro, expression, homology and predicted secondary structure data.
A framework for ontology-based access to biological data. It consists of a repository of (bio)ontologies, a set of webservices that provide access to OWL reasoning over these ontologies, and several frontends that utilize the ontology repository and reasoning services to provide access to specific biological datasets.
Contact for this page: Dr. Amanda Clare,
Group Coordinator,
Bioinformatics Group,
Department of Computer Science,
Llandinam Building,
Aberystwyth University,
Aberystwyth,
Ceredigion,
SY23 3DB
Tel: +44 (0)1970 622424 Email: afc@aber.ac.uk
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