Computational Biology Core

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Bioinformatics tools, custom databases, experimental designs, data acquisition/archival/access methods and data analysis/interpretation methods have had and will continue to have great impact on the RCE progress and will be the deliverables of a bioinformatics program. It should be noted that new bioinformatics technologies are anticipated to be developed and they will be necessary to integrate and analyze the many diverse types of data, and ideas for these tools will come from the biological scientists working in the projects and cores as well as bioinformaticists in our core, but bioinformaticists will develop the solution. We also leverage the existing commercial and non-commercial systems (tools, databases, development environments) to speed the bioinformatics solution development, for maximum data exchange compatibility issues, such as security, and for robustness. In the previous grant period, we created numerous tools and databases, which have had tens of thousands of users, have analyzed over 25 large array-based datasets and have reported this work in 13 publications. The Specific Aims for this core are: 1) To develop applied computational biology resources-codes databases and interpretations of data-to facilitate advances in the understanding and characterization of Category A-C pathogens, validate the performance of the codes/databases either collaboratively or via wet lab testing/checking a sampling of results and to provide computational support for project investigators; 2) To apply our computer codes (new and pathogen adapted) to pre-compute a variety of data for Category A-C pathogens, including ORF amplification primers (PCR, qPCR), DMA chip oligonucleotide probes for re-sequencing and expression, a collection of text-based literature and its extracted and associated biomedical objects: 3) To construct a pathogen-specific, internet accessible, www-based bioinformatics tool set and data warehouse of utilities and make them available to facilitate intra- and inter- institutional collaborations among project and core personnel and others in the biothreat and emerging pathogen research community; 4) To provide an experimental design data analysis and interpretation collaborative service to RCE researchers, especially as it appears to data intensive studies such as pathogen or host expression, proteomics or genomics, and 5) To continue to expand and maintain computer servers to support this effort.