Evolutionary Bioinformatics: Making Meaning of Microbes, Molecules, Maps

Underlying Principles of Natural Selection in Network Evolution: Systems Biology Approach

“…These and other molecular networks, such as protein interaction networks and metabolic networks, are intensely studied because their characterization has been greatly facilitated by new techniques in genomics and bioinformatics (Jungck et al 2006). There has been significant progress in unraveling the transcriptional regulatory networks of various model organisms such as E. Coli and B. subtilis.…”

“…By using computation methods such as orthology methods and binding-site profile methods, information of transcriptional regulatory networks is obtained from model organisms to poorly studied organisms by exploiting the publicly available completely sequenced genomes (Babu et al 2006). The availability of the complete genome sequences of over 300 prokaryotes and the understanding of the structure of transcriptional regulatory networks have allowed us to address several fundamental questions on the evolution of transcriptional regulatory networks, which will provide us with an opportunity to identify the distinct evolutionary trends in shaping transcriptional regulatory networks at various levels of organization (Jungck et al 2006; Babu et al 2006). …”

Graph Theory for Systems Biology

“…However, a variety of good algorithms that reduce the time exist for finding the maximal cliques even in a very large network. Our colleague, Noppadon Khirpet, in Thailand has implemented this algorithm for us in a program appropriately named PC-Tree [20], which we hope to extend to handle larger data sets in the near future. Our colleague, Noppadon Khirpet, in Thailand has implemented this algorithm for us in a program appropriately named PC-Tree [20], which we hope to extend to handle larger data sets in the near future.…”

“…We have developed four software packages for handling biological data using interval graph-theoretic techniques: (a) javaBenzer [21,22] and (b) BioGrapher [23,24], with only passing reference to (c) PC-tree [20] (currently lacking a data interface), and (d) javaBenzer FoodWeb, which is more relevant to material presented by Cozzens [25] in the second chapter of this book. In the examples that follow, we demonstrate that many biological problems can indeed be addressed from a discrete perspective to yield meaningful insights.…”