Author : Luis Pera Fernandes
Publisher :
ISBN 13 :
Total Pages : 334 pages
Book Rating : 4.:/5 (757 download)
Book Synopsis Multiscale Analysis of Protein Interaction Networks by : Luis Pera Fernandes
Download or read book Multiscale Analysis of Protein Interaction Networks written by Luis Pera Fernandes and published by . This book was released on 2010 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: High-throughput proteomics has allowed for the drafting of large protein-interaction networks and systems biology devotes a large effort to the statistical analysis of these. But rather than just a 'dot' connected in a network, each protein is a complex and dynamic three-dimensional object with sophisticated bio-chemical properties. To capture the complexity of these networks I have followed a multiscale approach by performing analysis of networks at different levels: a) a microscopic level where I analysed structural properties of interacting proteins; b) a medium-scale level in which I focused on system specific sub-networks; c) a macroscopic level where I performed a large-scale statistical and topological characterisation of protein-protein interaction networks (PPINs). For the microscopic analysis I focused on a special class of proteins: hub proteins which, contrary to most proteins in a network, can be involved in a large number of interactions. To date, it is not clear which properties facilitate hub's promiscuity; therefore, I have investigated a number of structural properties that may differentiate hubs from non-hubs and studied how these relate to single and multi-interface hub's classification. While PPINs portray a global picture of protein's connectivity, a medium-scale detailed analysis of a particular cellular function may benefit from accurately selected sub-networks of knowledge (SNK). Such SNKs contain high confidence interactions and multiple sources of information for its nodes (proteins) such as tissue specific expression data, gene expression data, domain profiles and structural data. SNK analysis provides the basis for the identification of fundamental components and pathways that can be carefully selected to focus experimental research and for helping the design of new experiments.