Last update: Sep 2005

Contrasts are effective conceptual vehicles for learning processes such as correcting, highlighting, contrasting, and grouping central concepts. Thus, they are useful for exploring the unknown. They can provide much invaluable insights and explanations about the observed phenomena. For example, contrasts between proteins in terms of their biological interactions can reveal what similarities, divergences, and relations there are of the proteins, leading to additional useful insights about the underlying functional nature of the proteins.

A protein-protein contrast is a contrast between two proteins A and B, called as "focused proteins", which indicates that A but not B is involved in a biological property C, called as "presupposed property", or vice versa. Contrast information is often encoded by contrastive negation patterns such as "A but not B" in the biomedical literature. Such contrast not only explicitly describes a difference between focused proteins in terms of its presupposed property, but also implicitly indicates that the focused proteins are semantically similar. This combination of difference and similarity between proteins is useful for augmenting proteomics databases and also for discovering novel knowledge.

BioContrasts Database is a database with protein-protein contrastive information. The database currently contains 41,471 protein-protein contrasts, which are automatically extracted from MEDLINE abstracts. Proteins in this database are cross-linked to Swiss-Prot for the purpose of effectively enhancing biomedical resources such as KEGG, InterPro, and Gene Ontology. With the web interface provided in this homepage, users can search for contrastive information of proteins of interest with their Swiss-Prot IDs or their names. Users also can attempt knowledge discovery with protein-protein contrasts through several templates of user interface.

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NLP & CL Lab Korea Advanced Institute of Science and Technology (KAIST), South Korea
Knowledge Discovery Department Institute for Infocomm Research(I2R), Singapore