THE SUBSTRUCTURE SERVER

USING MEDICAL ONTOLOGIES

Use Ontology and ML for database integration

Muggleton and Tamaddoni-Nezhad

Bridge between two disparate databases

LIGAND (biochemical reactions)

Enzyme classification system (EC) = ontology

Automated ontology maintenance

Colton and Traganidas (MSc. Last year)

Gene Ontology (big project)

Use data to find links between GO terms

Equivalence and implication finding using HR

GENE ONTOLOGY DISCOVERY

55%

STUDYING BIOCHEMICAL NETWORKS

Use SLPs to find mappings between genomes

Map function of pairs of homologous proteins

E.g., mouse and human

Homology is probabilistic

Developed SLP learning algorithms

Initial results applying them in biological networks

Work by

Muggleton, Angeloupolos and Watanabe

CLOSED LOOP MACHINE LEARNING

Active learning

Information theoretic algorithm designs and chooses the most informative and lowest cost experiments to carry out

Implemented in the ASE-Progol system

Learning generates hypotheses

Being studied by Ali Hafiz (PhD)

Idea: use machine learning to guide experimentation

using a real robot geneticist in a cyclic process

Aims of current project: determine the function of genes

Cost savings of 2 to 4 times over alternatives

Upcoming Nature article

FUTURE DIRECTIONS FOR MACHINE LEARNING IN BIOINFORMATICS

In-silico modelling of complete organisms

Representation and reasoning at all levels

From patient to the molecule

Probabalistic models

For more complex biological processes

Such as biochemical pathways

BIOCHEMICAL PATHWAYS

1/120th of a biochemical network