About Us

The cycle of theory, experiment, and information is nowhere more important than in the life sciences, where we are learning how to piece together various levels of expertise into a global or systems-level understanding of biology. Statistical Bioinformatics is involved at each level: accumulation, organization, and analysis of biological data. Hypotheses that are initiated and tested can be refined, and new experiments formulated for the purpose of supplying more information.

Statistical Bioinformatics



Statistical Bioinformatics



First Column: The Central Dogma lies at the heart of all biological investigations. Genes are transcribed, and then translated into proteins which in turn have a direct impact on the organism under investigation. Understanding the interrelated connections between DNA, gene, and protein toward function is one of the greatest biological mysteries remaining.

Second Column: Attached to each level of the Central Dogma is a new technology that allows an in depth measurement of that piece of the process. As such, DNA sequencing has allowed the complete sequencing of many genomes, including the human genome, which in turn allows the identification of every gene in an organism. However, knowing and understanding the function of every gene remains at bay. New technologies referred to as transcript profiling, or microarray technology, allow the simultaneous assessment of transcript abundance for every gene in a genome. While detecting changes in transcript abundance across conditions will not lead us to the function of genes, it does provide strong clues into the mechanisms that are involved. Although in its infancy an even newer technology that has an even wider appeal is known as protein microarrays, or proteomics. Protein arrays have great potential to provide strong links between the genes that encode for proteins and the end result/phenotype.

Third Column: New technologies enable genomic hypotheses to be formulated at each stage of the Central Dogma. Addressing individual questions uniquely supplies some limited information, but is restricted by the lack of connection between the stages of the biological process. Using Statistical Bioinformatics the data supplied by each new technology at each stage of the Central Dogma have great potential to be gathered from their individual sources into a single analysis of any biological process to provide avenues of gene networks, thus taking us from DNA sequence and gene to phenotypic result.