Biology – Quantitative Biology – Molecular Networks
Scientific paper
2006-07-18
Biology
Quantitative Biology
Molecular Networks
22 pages, 4 figures, accepted for publication in Physica A (2006)
Scientific paper
10.1016/j.physa.2006.04.118
We present the methods and results of a two-stage modeling process that generates candidate gene-regulatory networks of the bacterium B. subtilis from experimentally obtained, yet mathematically underdetermined microchip array data. By employing a computational, linear correlative procedure to generate these networks, and by analyzing the networks from a graph theoretical perspective, we are able to verify the biological viability of our inferred networks, and we demonstrate that our networks' graph theoretical properties are remarkably similar to those of other biological systems. In addition, by comparing our inferred networks to those of a previous, noisier implementation of the linear inference process [17], we are able to identify trends in graph theoretical behavior that occur both in our networks as well as in their perturbed counterparts. These commonalities in behavior at multiple levels of complexity allow us to ascertain the level of complexity to which our process is robust to noise.
Albert Reka
Christensen Charlotte
Gupta Anupam
Maranas Costas D.
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