protein interaction networks computational analysis

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Protein Interaction Networks

Author : Aidong Zhang
ISBN : 9780521888950
Genre : Computers
File Size : 90. 84 MB
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The first full survey of statistical, topological, data-mining, and ontology-based methods for analyzing protein-protein interaction networks.

Protein Protein Interactions And Networks

Author : Anna Panchenko
ISBN : 1848001258
Genre : Science
File Size : 51. 1 MB
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The biological interactions of living organisms, and protein-protein interactions in particular, are astonishingly diverse. This comprehensive book provides a broad, thorough and multidisciplinary coverage of its field. It integrates different approaches from bioinformatics, biochemistry, computational analysis and systems biology to offer the reader a comprehensive global view of the diverse data on protein-protein interactions and protein interaction networks.

Computational Prediction Of Protein Complexes From Protein Interaction Networks

Author : Sriganesh Srihari
ISBN : 9781970001532
Genre : Science
File Size : 48. 69 MB
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Complexes of physically interacting proteins constitute fundamental functional units that drive almost all biological processes within cells. A faithful reconstruction of the entire set of protein complexes (the "complexosome") is therefore important not only to understand the composition of complexes but also the higher level functional organization within cells. Advances over the last several years, particularly through the use of high-throughput proteomics techniques, have made it possible to map substantial fractions of protein interactions (the "interactomes") from model organisms including Arabidopsis thaliana (a flowering plant), Caenorhabditis elegans (a nematode), Drosophila melanogaster (fruit fly), and Saccharomyces cerevisiae (budding yeast). These interaction datasets have enabled systematic inquiry into the identification and study of protein complexes from organisms. Computational methods have played a significant role in this context, by contributing accurate, efficient, and exhaustive ways to analyze the enormous amounts of data. These methods have helped to compensate for some of the limitations in experimental datasets including the presence of biological and technical noise and the relative paucity of credible interactions. In this book, we systematically walk through computational methods devised to date (approximately between 2000 and 2016) for identifying protein complexes from the network of protein interactions (the protein-protein interaction (PPI) network). We present a detailed taxonomy of these methods, and comprehensively evaluate them for protein complex identification across a variety of scenarios including the absence of many true interactions and the presence of false-positive interactions (noise) in PPI networks. Based on this evaluation, we highlight challenges faced by the methods, for instance in identifying sparse, sub-, or small complexes and in discerning overlapping complexes, and reveal how a combination of strategies is necessary to accurately reconstruct the entire complexosome.

Biological Data Mining In Protein Interaction Networks

Author : Li, Xiao-Li
ISBN : 9781605663999
Genre : Technology & Engineering
File Size : 83. 86 MB
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"The goal of this book is to disseminate research results and best practices from cross-disciplinary researchers and practitioners interested in, and working on bioinformatics, data mining, and proteomics"--Provided by publisher.

Data Management Of Protein Interaction Networks

Author : Mario Cannataro
ISBN : 9781118103739
Genre : Computers
File Size : 51. 49 MB
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Current PPI databases do not offer sophisticated querying interfaces and especially do not integrate existing information about proteins. Current algorithms for PIN analysis use only topological information, while emerging approaches attempt to exploit the biological knowledge related to proteins and kinds of interaction, e.g. protein function, localization, structure, described in Gene Ontology or PDB. The book discusses technologies, standards and databases for, respectively, generating, representing and storing PPI data. It also describes main algorithms and tools for the analysis, comparison and knowledge extraction from PINs. Moreover, some case studies and applications of PINs are also discussed.

Experimental And Computational Analysis Of The Structure And Dynamics Of Intrinsically Disordered Proteins

Author : Elio Anthony Cino
ISBN : OCLC:1072016823
Genre :
File Size : 69. 80 MB
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Intrinsically disordered proteins (IDPs) are abundant in cells and have central roles in protein-protein interaction networks. Many are involved in cancer, aging and neurodegenerative diseases. The structure and dynamics of IDPs is intimately related to their interactions with binding partners. Because IDPs are inherently flexible and do not have a single conformation, conventional methods and conditions for determining structure and dynamics of globular proteins may not be directly applicable. Nuclear magnetic resonance (NMR) spectroscopy is one of the primary techniques characterizing the structures and dynamics of IDPs, but one cannot rely solely on NMR data. A primary aim of this work was to use Molecular Dynamics (MD) simulations in conjunction with NMR and other biophysical techniques to achieve a deeper understanding of the structure and dynamics of IDPs. To establish suitable parameters and force field choice for simulating IDPs, extensive MD simulations were performed and the results were compared to experimental data. Using computational and experimental techniques, the interactions between peptides from 9 disordered proteins with a common target were interrogated. The findings allowed us to determine key factors in modulating the affinities of the various interactions and highlighted the importance of molecular recognition fragments (MoRFs) in IDP target recognition and binding. IDP binding was also investigated from the perspective of the binding partner. The backbone resonances of the 3̃2 kDa target were assigned and the binding interface was mapped in the presence of a peptide from a disordered binding partner. Chemical shift changes distant from the interaction site indicated that IDP binding is a complex process, which should be studied from the perspectives of the partner and target. Because IDPs are highly sensitive to environmental conditions, the effects of molecular crowding on the dynamics of IDPs were also investigated. I found that crowding might have differential effects on the conformational propensities of distinct regions of some IDPs. This information will help to understand the behavior of IDPs in cellular environments and to determine suitable conditions for accurately studying them. This work has helped to improve the understanding of how IDP structure and dynamics relate to target binding.

Computational Systems Biology Of Pathogen Host Interactions

Author : Saliha Durmuş
ISBN : 9782889198214
Genre :
File Size : 46. 25 MB
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A thorough understanding of pathogenic microorganisms and their interactions with host organisms is crucial to prevent infectious threats due to the fact that Pathogen-Host Interactions (PHIs) have critical roles in initiating and sustaining infections. Therefore, the analysis of infection mechanisms through PHIs is indispensable to identify diagnostic biomarkers and next-generation drug targets and then to develop strategic novel solutions against drug-resistance and for personalized therapy. Traditional approaches are limited in capturing mechanisms of infection since they investigate hosts or pathogens individually. On the other hand, the systems biology approach focuses on the whole PHI system, and is more promising in capturing infection mechanisms. Here, we bring together studies on the below listed sections to present the current picture of the research on Computational Systems Biology of Pathogen-Host Interactions: - Computational Inference of PHI Networks using Omics Data - Computational Prediction of PHIs - Text Mining of PHI Data from the Literature - Mathematical Modeling and Bioinformatic Analysis of PHIs Computational Inference of PHI Networks using Omics Data Gene regulatory, metabolic and protein-protein networks of PHI systems are crucial for a thorough understanding of infection mechanisms. Great advances in molecular biology and biotechnology have allowed the production of related omics data experimentally. Many computational methods are emerging to infer molecular interaction networks of PHI systems from the corresponding omics data. Computational Prediction of PHIs Due to the lack of experimentally-found PHI data, many computational methods have been developed for the prediction of pathogen-host protein-protein interactions. Despite being emerging, currently available experimental PHI data are far from complete for a systems view of infection mechanisms through PHIs. Therefore, computational methods are the main tools to predict new PHIs. To this end, the development of new computational methods is of great interest. Text Mining of PHI Data from Literature Despite the recent development of many PHI-specific databases, most data relevant to PHIs are still buried in the biomedical literature, which demands for the use of text mining techniques to unravel PHIs hidden in the literature. Only some rare efforts have been performed to achieve this aim. Therefore, the development of novel text mining methods specific for PHI data retrieval is of key importance for efficient use of the available literature. Mathematical Modeling and Bioinformatic Analysis of PHIs After the reconstruction of PHI networks experimentally and/or computationally, their mathematical modeling and detailed computational analysis is required using bioinformatics tools to get insights on infection mechanisms. Bioinformatics methods are increasingly applied to analyze the increasing amount of experimentally-found and computationally-predicted PHI data.

Research In Computational Molecular Biology

Author : Terence Terry Speed
ISBN : 9783540716808
Genre : Science
File Size : 21. 34 MB
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This book constitutes the refereed proceedings of the 11th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2007, held in Oakland, CA, USA in April 2007. The 37 revised full papers address all current issues in algorithmic, theoretical, and experimental bioinformatics.

Kurventheorie

Author : Karl Menger
ISBN : 0828401721
Genre : Curves
File Size : 42. 26 MB
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This classic book is a treatise on the topology of curves. The class of curves considered is quite broad, including smooth curves, rational curves, trees, Cantor curves and so on. It was one of a small handful of landmark books on topology, in particular point-set topology, that were published during the important period of the 1930s. Many of the properties of curves explored by Menger are of renewed importance today in various contexts, notably the topology of dynamics.

Modern Genome Annotation

Author : D. Frishman
ISBN : 9783211751237
Genre : Science
File Size : 82. 80 MB
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An accurate description of current scientific developments in the field of bioinformatics and computational implementation is presented by research of the BioSapiens Network of Excellence. Bioinformatics is essential for annotating the structure and function of genes, proteins and the analysis of complete genomes and to molecular biology and biochemistry. Included is an overview of bioinformatics, the full spectrum of genome annotation approaches including; genome analysis and gene prediction, gene regulation analysis and expression, genome variation and QTL analysis, large scale protein annotation of function and structure, annotation and prediction of protein interactions, and the organization and annotation of molecular networks and biochemical pathways. Also covered is a technical framework to organize and represent genome data using the DAS technology and work in the annotation of two large genomic sets: HIV/HCV viral genomes and splicing alternatives potentially encoded in 1% of the human genome.

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