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Issue No. 05 - Sept.-Oct. (2012 vol. 9)
ISSN: 1545-5963
pp: 1293-1300
Richard Rottger , Comput. Syst. Biol. Group, Max Planck Institutefor Inf., Saarbrucken, Germany
Ulrich Ruckert , Dept. of Electr. Eng. & Comput. Sci., Univ. of California, Berkeley, CA, USA
Jan Taubert , Dept. of Comput. & Syst. Biol., Rothamsted Res., Harpenden, UK
Jan Baumbach , Comput. Syst. Biol. Group, Max Planck Institutefor Inf., Saarbrucken, Germany
The National Center for Biotechnology Information (NCBI) recently announced the availability of whole genome sequences for more than 1,000 species. And the number of sequenced individual organisms is growing. Ongoing improvement of DNA sequencing technology will further contribute to this, enabling large-scale evolution and population genetics studies. However, the availability of sequence information is only the first step in understanding how cells survive, reproduce, and adjust their behavior. The genetic control behind organized development and adaptation of complex organisms still remains widely undetermined. One major molecular control mechanism is transcriptional gene regulation. The direct juxtaposition of the total number of sequenced species to the handful of model organisms with known regulations is surprising. Here, we investigate how little we even know about these model organisms. We aim to predict the sizes of the whole-organism regulatory networks of seven species. In particular, we provide statistical lower bounds for the expected number of regulations. For Escherichia coli we estimate at most 37 percent of the expected gene regulatory interactions to be already discovered, 24 percent for Bacillus subtilis, and <;3% human, respectively. We conclude that even for our best researched model organisms we still lack substantial understanding of fundamental molecular control mechanisms, at least on a large scale.
microorganisms, bioinformatics, biological techniques, cellular biophysics, DNA, genetics, genomics, bioinformatics, gene regulatory networks, National Center for Biotechnology Information, genome sequences, DNA sequencing technology, cell survival, cell reproduction, transcriptional gene regulation, direct juxtaposition, Escherichia coli, Bacillus subtilis, fundamental molecular control mechanisms, Estimation, Databases, Bioinformatics, Robustness, Genomics, Humans, transcriptional gene regulatory networks., Computational biology, network statistics

J. Taubert, U. Ruckert, J. Baumbach and R. Rottger, "How Little Do We Actually Know? On the Size of Gene Regulatory Networks," in IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 9, no. , pp. 1293-1300, 2012.
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