Abstract </head> <body text="#000000" bgcolor="#FFFFFF" link="#0000EF" vlink="#CF30CF" alink="#FF0000" nosave> <br> <center><h2> Network approaches and microbial metabolism </h2> <br> <h2> Eivind Almaas </h2> <h3> (Network Biology, Microbial Systems Group, Lawrence Livermore National Laboratory) </h3> </center> <br> Network approaches have provided non-trivial insight on the organization of many biological systems. In the case of cellular metabolism, where nodes correspond to metabolites and links indicate chemical reactions, it is frequently possible to facilitate close interactions between experiments and computational modeling. Using a "flux-balance" modeling approach, one may predict metabolic flux (or link weight) patterns on the organism-level, and study the effect of network topology on cellular function and robustness. In this presentation, I will discuss basics of metabolic network modeling and flux-balance calculations, using examples from the whole-cell network reconstructions of metabolism in the bacterium <i>Escherichia coli</i> and the yeast <i>Saccharomyces cerevisiae</i>. Our metabolic analysis has uncovered that, since the connectivity distribution for all known metabolic networks is scale-free, the possible flux distributions are characterized by a heavy-tail. Most recently, we have used this modeling framework to study epistasis, the non-linear interaction between genes as mediated by the metabolic network. <br><br><br> <a href="index.html">Back to main page</a><br><br> <hr> <p><br><br> </body> </html>