Modeling Biological Networks

IV.1 Coordinators
IV.2 Participants
IV.3 Introduction
IV.4 Background and Significance
IV.5 Research Plan
IV.6 Specific Subprojects

• IV.6.iii Subproject 3 Regulatory Words in Eukaryotic Genomes:
  • IV.6.iii.a Introduction
  • IV.6.iii.b Methodology
  • IV.6.iii.c Research Plan
• [ Other Subprojects ]

IV.7 Connection to Specific Projects 2 (cytoskeleton) and 3 (organogenesis)
IV.8 Timeline

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IV.6.iii.c Research Plan:
Aim 1. Identify "candidate words". We will test all words of length [4-12] Np and the whole Drosophila genome. If Drosophila proves too difficult, we will move to the existing yeast data quickly. If not, we will still seek to compare our results with yeast data as we go along. We will develop the necessary statistical tests.

Aim 2. Look at the spatial correlations among candidate words. This will necessarily be selective, but it will follow a logical pattern dictated by biological knowledge and statistical certainty.

Aim 3. Identify and map clusters using the methods in Subproject 1 and look for correlations between clusters and promoters using the current Drosophila annotation.

Aim 4. Disseminate these mapping data by publication and on the CGB web site.

If successful, our approach will identify new transcription factor binding sites, shed light on the use of degenerate sites, and - most importantly - provide both cluster maps and a tool for generating them.