Modular decomposition of protein-protein interaction networks

We introduce an algorithmic method, termed modular decomposition, that defines the organization of protein-interaction networks as a hierarchy of nested modules. Modular decomposition derives the logical rules of how to combine proteins into the actual functional complexes by identifying groups of proteins acting as a single unit (sub-complexes) and those that can be alternatively exchanged in a set of similar complexes. The method is applied to experimental data on the pro-inflammatory tumor necrosis factor-α (TNF-α)/NFκB transcription factor pathway

Computational comparisons of model genomes

Complete genomes from model organisms provide new challenges for computational molecular biology. Novel questions emerge from the genome data obtained from the functional prediction of thousands of gene products. In this review, we present some approaches to the computational comparison of genomes, based on sequence and text analysis, and comparisons of genome composition and gene order. With the recent publication of the complete genome sequences from two bacteria, Haemophilus injuenzae Rdi and Mycoplasma genitalium2, new challenges are emerging for computational biology. Two such challenges are (1) to predict and annotate the fimctions of the gene products as rapidly and completely as possible, and (2) to derive adequate abstractions that make genomes comparable at a higher-than-molecular level