Although there exists some works, for example [ 11], which apply sparse coding in the classification of biological data, to the best of our knowledge, this is the first time that sparse representation is intensively and systematically studied in the area of bioinformatics.
Translational bioinformatics is an emerging field that aims to exploit various kinds of biological data for useful knowledge to be translated into clinical practice.
In modern time, manual curation of databases is made to ensure transmission of biological data and knowledge.
This testbed represents another step in advancing standards-based processes in the bioinformatics community which is essential to the growing interoperability of biological data, information, knowledge and computational resources.
Although essential to retain as a thoroughly developed biological data model, knowledge representation, and accepted community standard, the existing PGDB framework is not well suited when combined with automated genome annotation pipelines to generate representations of metabolic pathways that include sub-cellular localization of the enzymes and metabolites in the pathways.
In case of real biological data, prior knowledge derived from gene ontologies or ChIP analysis can be used in order to restrict the set of possible regulators.
We have developed a novel IMP-WFDR method that derives weights from a state-of-the-art data integration algorithm and incorporates them in WFDR to more effectively account for multiple test given the context of available biological data and knowledge.
This indicates that our proposed method can identify more biologically relevant genes than an unweighted FDR method, which ignores existing biological data and knowledge.
(Researchers dealing with large-scale data may want to consider the 'Semantic Web', which is becoming a new standard for representation of biological data and knowledge.
Our method intertwines stringency level settings, biological data and a knowledge database to highlight molecular interactions using networks and pathways.
