New strategy for the representation and the integration of biomolecular knowledge at a cellular scale.

ABSTRACT: The combination of sequencing and post-sequencing experimental approaches produces huge collections of data that are highly heterogeneous both in structure and in semantics. We propose a new strategy for the integration of such data. This strategy uses structured sets of sequences as a unified representation of biological information and defines a probabilistic measure of similarity between the sets. Sets can be composed of sequences that are known to have a biological relationship (e.g. proteins involved in a complex or a pathway) or that share similar values for a particular attribute (e.g. expression profile). We have developed a software, BlastSets, which implements this strategy. It exploits a database where the sets derived from diverse biological information can be deposited using a

SUBMITTER: Barriot R 

PROVIDER: S-EPMC484170 | biostudies-literature | 2004

REPOSITORIES: biostudies-literature