A model of large-scale proteome evolution

The next step in the understanding of the genome organization, after the determination of complete sequences, involves proteomics. The proteome includes the whole set of protein-protein interactions, and two recent independent studies have shown that its topology displays a number of surprising features shared by other complex networks, both natural and artificial. In order to understand the origins of this topology and its evolutionary implications, we present a simple model of proteome evolution that is able to reproduce many of the observed statistical regularities reported from the analysis of the yeast proteome. Our results suggest that the observed patterns can be explained by a process of gene duplication and diversification that would evolve proteome networks under a selection pressure, favoring robustness against failure of its individual components

Comparative genomic analysis of novel Acinetobacter symbionts : A combined systems biology and genomics approach

Acknowledgements This work was supported by University of Delhi, Department of Science and Technology- Promotion of University Research and Scientific Excellence (DST-PURSE). V.G., S.H. and U.S. gratefully acknowledge the Council for Scientific and Industrial Research (CSIR), University Grant Commission (UGC) and Department of Biotechnology (DBT) for providing research fellowship.Peer reviewedPublisher PD

Wavelet analysis on symbolic sequences and two-fold de Bruijn sequences

The concept of symbolic sequences play important role in study of complex systems. In the work we are interested in ultrametric structure of the set of cyclic sequences naturally arising in theory of dynamical systems. Aimed at construction of analytic and numerical methods for investigation of clusters we introduce operator language on the space of symbolic sequences and propose an approach based on wavelet analysis for study of the cluster hierarchy. The analytic power of the approach is demonstrated by derivation of a formula for counting of {\it two-fold de Bruijn sequences}, the extension of the notion of de Bruijn sequences. Possible advantages of the developed description is also discussed in context of applied

Application of regulatory sequence analysis and metabolic network analysis to the interpretation of gene expression data

We present two complementary approaches for the interpretation of clusters of co-regulated genes, such as those obtained from DNA chips and related methods. Starting from a cluster of genes with similar expression profiles, two basic questions can be asked: 1. Which mechanism is responsible for the coordinated transcriptional response of the genes? This question is approached by extracting motifs that are shared between the upstream sequences of these genes. The motifs extracted are putative cis-acting regulatory elements. 2. What is the physiological meaning for the cell to express together these genes? One way to answer the question is to search for potential metabolic pathways that could be catalyzed by the products of the genes. This can be done by selecting the genes from the cluster that code for enzymes, and trying to assemble the catalyzed reactions to form metabolic pathways. We present tools to answer these two questions, and we illustrate their use with selected examples in the yeast Saccharomyces cerevisiae. The tools are available on the web (http://ucmb.ulb.ac.be/bioinformatics/rsa-tools/; http://www.ebi.ac.uk/research/pfbp/; http://www.soi.city.ac.uk/~msch/)