I. King Jordan
Associate Professor
School of Biology
Georgia Institute of Technology
I came to Georgia Tech in August 2006 after six years at the National Center for Biotechnology Information (NCBI). The Evolutionary Systems Biology Group was formed shortly thereafter when Bioinformatics PhD student Jittima Piriyapongsa joined the lab. There are currently 10 members of the group including undergrad, Masters and PhD students.
Members of the ESBG investigate genomic evolution, dynamics and systems through the computational analysis of large-scale molecular data sets. The techniques we employ include comparative genomic sequence analysis as well as the interrogation of functional data such as expression patterns, protein interactions and gene knock-out effects. To a certain extent our efforts are theoretically driven, but we are firmly grounded in empirics, i.e. the analysis of real experimentally characterized data. For us, Systems Biology entails an emphasis on understanding the interactions among the numerous players that unite to carry out biological function: genes, transcripts and proteins in particular. By integrating diverse sources of biological data, we would like to be able to uncover genome-level determinants that specify evolutionary trajectories at higher orders of biological organization along with the genome dynamics that are related to cellular transitions from normal to disease states. It is our hope that this kind of work will allow us to move towards a more unified, and deterministic, understanding of biology.
The comparative emphasis of our research necessitates the analysis of data from many different species. Much of our work on genome dynamics is done on eukaryotes with an emphasis on the human genome. Our efforts in computational genomics are focused primarily on microbial genomes.
We are currently working on three specific areas of research:
- Transposition - the influence of transposable elements (TEs) on the structure, function and evolution of eukaryotic genomes. Understanding the relationship between TEs, chromatin structure and gene expression.
- Regulation - the tempo and mode of evolutionary changes in patterns of gene regulation and expression as well as the evolutionary origins of regulatory RNAs. Defining changes in gene expression that distinguish normal from cancerous tissue(s).
- Computational Genomics - the development and application of computational tools for analysis of microbial genome sequences. Creation of web-enabled programs for the molecular epidemiological analysis of microbial pathogens.