Bioinformatics Software Development Projects

Large-Scale Systems Biology Research at OSC

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Description:
Traditional molecular biology approach to study gene expression and gene regulation is based on an ad hoc individual analysis that is very laborious. Moreover, the data collected in this way is of isolated status and thus may not truly reflect the real characteristics of the cell or organism. With the advent of genome sequencing and high-throughput measurement technologies, comprehensive data can be collected at the system level or at the whole genome-scale. Particularly, gene expression microarray technology is revolutionizing many aspects of biological research as it allows monitoring many thousands of gene transcripts simultaneously. This provides powerful tools for the genome-wide correlation of gene transcript levels with physiological responses and alterations in physiological states to assess various biological models, including disease, therapy, or experimental manipulation. Recently, chromatin immunoprecipitation technology has been coupled with the high-throughput DNA microarray (CHIP-on-Chip) to study the protein-DNA binding assay at the genome-scale level. With the combined high-throughput data in both gene expression and bind assay, the gene regulatory network could be solidly constructed at the genome-wide level using sophisticated computer algorithms, such as GRAM, REDUCE, modified MOTIF REGRESSOR, etc.

OSC has been integrating a Systems Biology infrastructure to assist Ohioan and national biological researchers in Genomics, Computation, Analysis, and Technology. Using field programmable gate array technology with de novo software development, OSC has developed a unique DNA microarray design algorithm and the first equine GeneChip has been designed. Collaborated with OSU researchers, OSC has developed the CHIP-on-Chip technology which allows us to make extensive collaboration within the state and nationwide. Collaboration with the researchers from the University of Texas Medical Branch and the University of Pittsburgh Cancer Institute has been established. A comprehensive infrastructure for bioinformatics data analysis, data model, data simulation and data prediction is being constructed at OSC to provide strong support to experimental biologists for data validation and new research hypothesis creation.

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