Computational Bio & Bioinformatics Discussion Group
Posted March 13, 2010
Many organisms share the same genes but they are regulated in a variety of ways and at different times, resulting in vastly different species—say, a human versus a mouse. Along with identifying genes, it is therefore critical to understand noncoding regulatory DNA sequences and the proteins that turn them on and off. These proteins, known as transcription factors, work by binding to specific DNA sequences upstream of the genes they regulate, signaling the genes to turn on their expression. These integral biomolecules vary widely to affect thousands of different genes in species that are evolutionarily far apart. Yet all transcription factors stem from just a few scaffold structures.
In an effort to identify a comprehensive set of transcription factors, along with their binding sites, given a specific genome sequence, many researchers have developed experimental technologies like chip-chip techniques and DNA microarrays that bind proteins. Joel Bader of Johns Hopkins University is approaching the problem from a computational perspective. He described his work at a meeting of the Computational Bio & Bioinformatics Discussion Group.
Use the tabs above to view the meeting report.
This database, designed at the Bader Laboratory, allows you to use your favorite genes as anchors for building a network from Drosophila protein-protein interactions, detected experimentally or mapped cross-species from Saccharomyces orthologs.
This Web site outlines plans to completely resynthesize the DNA in a yeast cell.
Bader, J. S. 2003. Greedily building protein networks with confidence. Bioinformatics 19: 1869-1874. (PDF, 140 KB) FULL TEXT
Bader, J. S., A. Chaudhuri, J. M. Rothberg & J. Chant. 2004. Gaining confidence in high-throughput protein interaction networks. Nat. Biotechnol. 22: 78-85.
Bader, J. S. & J. Chant. 2006. When proteomes collide. Science 311: 187.
Giot, L., J. S. Bader, C. Brouwer, et al. 2003. A protein interaction map of Drosophila melanogaster. Science 302: 1727-1736.
Liu, A. & J. S. Bader. 2006. Decoding transcriptional regulatory interactions. Physica D (in press).
Qi, Y., P. Ye & J. S. Bader 2005. Genetic Interaction Motif Finding by expectation maximization—a novel statistical model for inferring gene modules from synthetic lethality. BMC Bioinformatics 6: 288. FULL TEXT
Pan, X., P. Ye, D. S. Yuan, et al. 2006. A DNA integrity network in the yeast Saccharomyces cerevisiae. Cell 124: 973-983.
Ye, P., B. D. Peyser, F. A. Spencer & J. S. Bader. 2005. Commensurate distances and similar motifs in genetic congruence and protein interaction networks in yeast. BMC Bioinformatics 6: 270. FULL TEXT
Ye, P., B. D. Peyser, X. Pan, et al. 2005. Gene function prediction from congruent synthetic lethal interactions in yeast. Mol. Syst. Bio. 1: 2005.0026. FULL TEXT
Joel S. Bader, PhD
Johns Hopkins University
email | web site | publications
Joel Bader is an assistant professor in the Department of Biomedical Engineering at Johns Hopkins University.
Kiryn Haslinger is a science writer and editor with a masters in theoretical chemistry. Since working with James D. Watson on his book DNA: The Secret of Life as a research and editorial assistant, she has written freelance articles on science and scientific history.