Bioinformatics and Computational Biology

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An example of research created by our Bioinformatics and Computational Biology Cohort:
“Hungry Monsters: A Computational Model for the Evolution of Metabolic Gene Regulation”
Caleb Simmons
Associate Professor Dr. Ivan Erill
Associate Professor Dr. Muruhan Rathinam

Prokaryotic cells live in variable environments where information signals may fluctuate rapidly. These cells employ the use of transcription factors to regulate gene expression in response to these noisy signals. The interaction between transcription factors and genes form Gene Regulatory Networks, and these networks feature commonly repeated patterns known as network motifs. It has been hypothesized that many of these motifs have evolved because they efficiently deal with transient signalling from the environment. To confirm this hypothesis we have developed a computational model of the evolution of Gene Regulatory Networks that deal with sugar metabolism in a variety of environments. The model describes the dynamics of gene regulation and the evolution of network structure. The primary aim of this model is to identify efficient network structures and to determine how these structures are derived by natural selection.

This work was funded through NSF Grant No. DBI 1031420 – Undergraduate Biology Math Training Program.

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Benefits for Bioinformatics and Computational Biology students:

  • Work with a faculty member
  • Experience hands-on research
  • Reinforce classroom learning
  • Prepare for work or graduate school
  • Travel to national conferences
  • Receive grant funding
  • Publish independent research
    • Characterization of the SOS meta-regulon in the human gut microbiome.
      Cornish JP, Sanchez-Alberola N, O’Neill PK, O’Keefe R, Gheba J, Erill I.
      Bioinformatics. 2014 May 1;30(9):1193-7.
    • CollecTF: a database of experimentally validated transcription factor-binding sites in Bacteria. Kiliç S, White ER, Sagitova DM, Cornish JP, Erill I.
      Nucleic Acids Res. 2014 Jan;42(Database issue):D156-60.
    • scnRCA: a novel method to detect consistent patterns of translational selection in mutationally-biased genomes. O’Neill PK, Or M, Erill I.
      PLoS One. 2013 Oct 7;8(10):e76177.
    • Inference of self-regulated transcriptional networks by comparative genomics.
      Cornish JP, Matthews F, Thomas JR, Erill I.
      Evol Bioinform Online. 2012;8:449-61.
    • BioWord: a sequence manipulation suite for Microsoft Word.
      Anzaldi LJ, Muñoz-Fernández D, Erill I.
      BMC Bioinformatics. 2012 Jun 7;13:124

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