Inverse problems in statistical physics are motivated by the challenges of 'big data'in
different fields, in particular high-throughput experiments in biology. In inverse problems, the …

In order to understand the functioning of organisms on the molecular level, we need to know
which genes are expressed, when and where in the organism, and to which extent. The …

Gene co-expression networks can be used to associate genes of unknown function with
biological processes, to prioritize candidate disease genes or to discern transcriptional …

Systematic perturbation of cells followed by comprehensive measurements of molecular and
phenotypic responses provides informative data resources for constructing computational …

Praise for the first edition:… superb, beautifully written and organized work that takes an
engineering approach to systems biology. Alon provides nicely written appendices to …

Background Co-expression measures are often used to define networks among genes.
Mutual information (MI) is often used as a generalized correlation measure. It is not clear …

Motivation: Our goal is to construct a model for genetic regulatory networks such that the
model class:(i) incorporates rule-based dependencies between genes;(ii) allows the …

Heat maps and clustering are used frequently in expression analysis studies for data
visualization and quality control. Simple clustering and heat maps can be produced from the …

A network of interactions is called modular if it is subdivided into relatively autonomous,
internally highly connected components. Modularity has emerged as a rallying point for …

Much of a cell's activity is organized as a network of interacting modules: sets of genes
coregulated to respond to different conditions. We present a probabilistic method for …