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Semantic Modeling of Biological Sequences and Bioinformatics

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E ssential to the field of bioinformatics, biosequence databases play a key role in the success of the Human Genome Project (HGP). With the extraordinary amount of data generated by the HGP, the post-HGP era is in urgent need of reliable, flexible, and convenient data management techniques. Effective data management will assist biology/genetics researchers in decoding the data in gene and protein sequences and answering important questions concerning life, health, and environment. Numerous sequence databases exist globally, they have been constructed using different data models, but none of them has the ability to easily and intuitively answer ad hoc or complex queries. This has become a serious bottleneck for users whose research problems are getting more and more sophisticated. In this work we propose several new semantic constructs to model the complexity of biological sequence data and 3-D protein structures. We propose the addition of spatial semantics and other constructs to represent the chemical forces that contribute to the formation of specific structures. Our work makes a contribution to modeling the specialty of life science data and develops methods to meet the novel challenges posed by such data. We believe our semantic model will facilitate more effective management of sequence data and enable processing of ad hoc and complex queries about biological sequences.

Please click HERE for a PowerPoint presentation of the project.

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