New Approaches of Protein Function Prediction from Protein Interaction Networks Book

New Approaches of Protein Function Prediction from Protein Interaction Networks

  • Author : Jingyu Hou
  • Publisher : Academic Press
  • Release Date : 2017-01-13
  • Genre: Mathematics
  • Pages : 124
  • ISBN 10 : 9780128099445

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New Approaches of Protein Function Prediction from Protein Interaction Networks contains the critical aspects of PPI network based protein function prediction, including semantically assessing the reliability of PPI data, measuring the functional similarity between proteins, dynamically selecting prediction domains, predicting functions, and establishing corresponding prediction frameworks. Functional annotation of proteins is vital to biological and clinical research and other applications due to the important roles proteins play in various biological processes. Although the functions of some proteins have been annotated via biological experiments, there are still many proteins whose functions are yet to be annotated due to the limitations of existing methods and the high cost of experiments. To overcome experimental limitations, this book helps users understand the computational approaches that have been rapidly developed for protein function prediction. Provides innovative approaches and new developments targeting key issues in protein function prediction Presents heuristic ideas for further research in this challenging area

Protein Function Prediction from Protein Interaction Network Book

Protein Function Prediction from Protein Interaction Network

  • Author : Sovan Saha
  • Publisher : LAP Lambert Academic Publishing
  • Release Date : 2013
  • Genre: Uncategoriezed
  • Pages : 148
  • ISBN 10 : 3659402788

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Proteins perform every function in a cell. With the advent of genome sequencing projects for different organisms, large amounts of DNA and protein sequence data is available, whereas their biological function is still unknown in the most of the cases. Predicting protein function is the most challenging problem in post-genomic era. Using sequence homology, phylogenetic profiles, gene expression data, and function of unknown protein can be predicted. Recently, the large interaction networks constructed from high throughput techniques like Yeast2Hybrid experiments are also used in prediction of protein function. As experimental techniques for detection and validation of protein interactions are time consuming, there is a need for computational methods for this task. Based on the concept that a protein performs similar function like its neighbor in protein interaction network, a method is proposed to predict protein function using protein-protein interaction data.This analysis should enlighten the path for predicting unannotated protein function hence identifying diseases and inventing methods of it's cureness.

Protein protein Interactions and Networks Book

Protein protein Interactions and Networks

  • Author : Anna Panchenko
  • Publisher : Springer Science & Business Media
  • Release Date : 2010-04-06
  • Genre: Science
  • Pages : 212
  • ISBN 10 : 1848001258

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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.

Functional Module Identification and Function Prediction from Protein Interaction Networks Book

Functional Module Identification and Function Prediction from Protein Interaction Networks

  • Author : Young-Rae Cho
  • Publisher : Unknown
  • Release Date : 2009
  • Genre: Uncategoriezed
  • Pages : 179
  • ISBN 10 : OCLC:639328387

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Since the completion of sequencing human genome, uncovering the principles of interactions and the functional roles of proteins has been in the spotlight in this post-genomic era. The interactions between proteins provide insights into the underlying mechanisms of biological processes within a cell. The functions of an unknown protein can be postulated on the basis of its interaction evidence with known proteins. The systematic analysis of protein interaction networks has thus become a primary issue in current Bioinformatics research. A wide range of graph theoretic or statistical approaches have attempted to effectively analyze the protein interaction networks. However, they had a limitation in accuracy and efficiency because of the challenges as following. First, the protein-protein interaction data, generated by large-scale high-throughput experiments, are not reliable. Next, the protein interaction networks are typically structured by complex connectivity.^Finally, each protein performs multiple functions in varying environmental conditions. In this dissertation, I explore the quantitative characterization of protein interaction networks based on their unique features such as small-world phenomenon, scale-free distribution and hierarchical modularity. In particular, I focus on accurate, efficient mining of protein interaction networks for the purpose of identifying functional modules and predicting protein functions. A functional module is defined as a maximal set of proteins that participate in the same function. As a pre-process, the network weighting is applied by the integration of functional knowledge from the Gene Ontology database. The semantic similarity and semantic interactivity measures estimate the interaction reliability, which is assigned to the corresponding edge as a weight.^These weighted interaction networks can facilitate the accurate analysis for functional knowledge discovery. I introduce four different approaches for functional module ident

Prediction of Protein Structures  Functions  and Interactions Book

Prediction of Protein Structures Functions and Interactions

  • Author : Janusz M. Bujnicki
  • Publisher : John Wiley & Sons
  • Release Date : 2008-12-23
  • Genre: Science
  • Pages : 302
  • ISBN 10 : 0470741902

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The growing flood of new experimental data generated by genome sequencing has provided an impetus for the development of automated methods for predicting the functions of proteins that have been deduced by sequence analysis and lack experimental characterization. Prediction of Protein Structures, Functions and Interactions presents a comprehensive overview of methods for prediction of protein structure or function, with the emphasis on their availability and possibilities for their combined use. Methods of modeling of individual proteins, prediction of their interactions, and docking of complexes are put in the context of predicting gene ontology (biological process, molecular function, and cellular component) and discussed in the light of their contribution to the emerging field of systems biology. Topics covered include: first steps of protein sequence analysis and structure prediction automated prediction of protein function from sequence template-based prediction of three-dimensional protein structures: fold-recognition and comparative modelling template-free prediction of three-dimensional protein structures quality assessment of protein models prediction of molecular interactions: from small ligands to large protein complexes macromolecular docking integrating prediction of structure, function, and interactions Prediction of Protein Structures, Functions and Interactions focuses on the methods that have performed well in CASPs, and which are constantly developed and maintained, and are freely available to academic researchers either as web servers or programs for local installation. It is an essential guide to the newest, best methods for prediction of protein structure and functions, for researchers and advanced students working in structural bioinformatics, protein chemistry, structural biology and drug discovery.

Protein Interaction Networks Book

Protein Interaction Networks

  • Author : Aidong Zhang
  • Publisher : Cambridge University Press
  • Release Date : 2009-04-06
  • Genre: Computers
  • Pages : 297
  • ISBN 10 : 9780521888950

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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 Book

Protein Protein Interactions

  • Author : Weibo Cai
  • Publisher : BoD – Books on Demand
  • Release Date : 2012-03-30
  • Genre: Science
  • Pages : 488
  • ISBN 10 : 9789535103974

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Proteins are indispensable players in virtually all biological events. The functions of proteins are coordinated through intricate regulatory networks of transient protein-protein interactions (PPIs). To predict and/or study PPIs, a wide variety of techniques have been developed over the last several decades. Many in vitro and in vivo assays have been implemented to explore the mechanism of these ubiquitous interactions. However, despite significant advances in these experimental approaches, many limitations exist such as false-positives/false-negatives, difficulty in obtaining crystal structures of proteins, challenges in the detection of transient PPI, among others. To overcome these limitations, many computational approaches have been developed which are becoming increasingly widely used to facilitate the investigation of PPIs. This book has gathered an ensemble of experts in the field, in 22 chapters, which have been broadly categorized into Computational Approaches, Experimental Approaches, and Others.

Protein Interaction Networks in Health and Disease Book

Protein Interaction Networks in Health and Disease

  • Author : Spyros Petrakis
  • Publisher : Frontiers Media SA
  • Release Date : 2016-10-19
  • Genre: Genetics
  • Pages : 91
  • ISBN 10 : 9782889199822

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The identification and mapping of protein-protein interactions (PPIs) is a major goal in systems biology. Experimental data are currently produced in large scale using a variety of high-throughput assays in yeast or mammalian systems. Analysis of these data using computational tools leads to the construction of large protein interaction networks, which help researchers identify novel protein functions. However, our current view of protein interaction networks is still limited and there is an active field of research trying to further develop this concept to include important processes: the topology of interactions and their changes in real time, the effects of competition for binding to the same protein region, PPI variation due to alternative splicing or post-translational modifications, etc. In particular, a clinically relevant topic for development of the concept of protein interactions networks is the consideration of mutant isoforms, which may be responsible for a pathological condition. Mutations in proteins may result in loss of normal interactions and appearance of novel abnormal interactions that may affect a protein’s function and biological cycle. This Research Topic presents novel findings and recent achievements in the field of protein interaction networks with a focus on disease. Authors describe methods for the identification and quantification of PPIs, the annotation and analysis of networks, considering PPIs and protein complexes formed by mutant proteins associated with pathological conditions or genetic diseases.

Network based Information Integration for Protein Function Prediction Book

Network based Information Integration for Protein Function Prediction

  • Author : Xiaoyu Jiang
  • Publisher : Unknown
  • Release Date : 2009
  • Genre: Uncategoriezed
  • Pages : 182
  • ISBN 10 : OCLC:606828841

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Abstract: Protein function prediction is a fundamental problem in computational biology. For protein activities described by terms in databases such as the Gene Ontology (GO), this task is typically pursued as a binary classification problem. As a result of an astonishing increase in the available genome-wide protein information, integrating different protein datasets has become a significant opportunity and a major focus to infer functionality. This dissertation contains three novel approaches to integrate popular protein information to classify proteins into functional categories. A probabilistic method, Hierarchical Binomial-Neighborhood (HBN), combining proteins' relational information from the protein-protein interaction (PPI) network, together with the GO hierarchical structure, is proposed first. Results from comparing analogous models on terms from the biological process ontology and genes from the yeast genome show substantial improvement and further analysis illustrates that such an improvement is uniformly consistent with the GO depth. Being aware of the fact that the gene interaction knowledge is still incomplete in most organisms, the second approach we develop is an aggressively integrative probabilistic framework, Probabilistic Hierarchical Inferences for Protein Activity (PHIPA), with improved data usage efficiency, for combining protein relational network, categorical motif and cellular localization information and the GO hierarchy. We implement it on a network extracted from an integrative protein-protein association databases STRING (Search Tool for the Retrieval of Interacting Genes/Proteins). Being based on Nearest-Neighbor, or the "guilt-by-association" counting principle, both HBN and PHIPA use only the local neighborhood information, and are therefore built on local probabilistic models. In contrast, we develop a third approach, a fully Bayesian network-based auto-probit framework encoding the functional similarity influenced by the network t

Development and Application of a Computational Approach to Align Protein Interaction Networks Book

Development and Application of a Computational Approach to Align Protein Interaction Networks

  • Author : Phan Thi Thu Hang
  • Publisher : Unknown
  • Release Date : 2012
  • Genre: Uncategoriezed
  • Pages : null
  • ISBN 10 : OCLC:827258296

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This thesis describes the development of PINALOG, a protein interaction network alignment method, and its application to the area of protein function prediction and protein complex detection. Protein-protein interactions (PPI) play an important role in the function of biological processes. Advances in high-throughput technology have produced a large amount of protein-protein interaction data, enabling analyses at the system level. Although protein-protein interaction networks (PPINs) vary between species, there are components of them that perform similar biological functions and these are likely to be conserved across species. Comparison of the protein interaction networks from different species yields understanding of the evolution of species, as well as a means to predict protein function and conserved components. An alignment method, PINALOG, has been developed which globally aligns the similar parts of the networks using information from protein sequences, protein functions and network topology in a seed-and-extend framework. The results on human and yeast network alignment revealed conserved subnetworks that are components of similar biological processes such as the proteasome or transcription related processes. The alignments of several pairs of species confirm the superior performance of PINALOG over commonly used methods such as Graemlin and IsoRank in terms of finding a large conserved network as well as detecting biologically meaningful mappings of the proteins in the two aligned species. The alignment method also suggested an approach to perform protein complex prediction by knowledge transfer from one species to another. In addition the implications for function prediction of proteins in the "twilight" zone where there is little or no sequence similarity were explored. A web server for PINALOG was developed to provide users access to the alignment method.

Biomolecular Networks Book

Biomolecular Networks

  • Author : Luonan Chen
  • Publisher : John Wiley & Sons
  • Release Date : 2009-06-29
  • Genre: Computers
  • Pages : 416
  • ISBN 10 : 0470488050

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Alternative techniques and tools for analyzing biomolecular networks With the recent rapid advances in molecular biology, high-throughput experimental methods have resulted in enormous amounts of data that can be used to study biomolecular networks in living organisms. With this development has come recognition of the fact that a complicated living organism cannot be fully understood by merely analyzing individual components. Rather, it is the interactions of components or biomolecular networks that are ultimately responsible for an organism's form and function. This book addresses the important need for a new set of computational tools to reveal essential biological mechanisms from a systems biology approach. Readers will get comprehensive coverage of analyzing biomolecular networks in cellular systems based on available experimental data with an emphasis on the aspects of network, system, integration, and engineering. Each topic is treated in depth with specific biological problems and novel computational methods: GENE NETWORKS—Transcriptional regulation; reconstruction of gene regulatory networks; and inference of transcriptional regulatory networks PROTEIN INTERACTION NETWORKS—Prediction of protein-protein interactions; topological structure of biomolecular networks; alignment of biomolecular networks; and network-based prediction of protein function METABOLIC NETWORKS AND SIGNALING NETWORKS—Analysis, reconstruction, and applications of metabolic networks; modeling and inference of signaling networks; and other topics and new trends In addition to theoretical results and methods, many computational software tools are referenced and available from the authors' Web sites. Biomolecular Networks is an indispensable reference for researchers and graduate students in bioinformatics, computational biology, systems biology, computer science, and applied mathematics.

Genome Wide Prediction and Analysis of Protein Protein Functional Linkages in Bacteria Book

Genome Wide Prediction and Analysis of Protein Protein Functional Linkages in Bacteria

  • Author : Vijaykumar Yogesh Muley
  • Publisher : Springer Science & Business Media
  • Release Date : 2012-07-28
  • Genre: Science
  • Pages : 60
  • ISBN 10 : 9781461447054

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​​ ​Using genome sequencing, one can predict possible interactions among proteins. There are very few titles that focus on protein-protein interaction predictions in bacteria. The authors will describe these methods and further highlight its use to predict various biological pathways and complexity of the cellular response to various environmental conditions. Topics include analysis of complex genome-scale protein-protein interaction networks, effects of reference genome selection on prediction accuracy, and genome sequence templates to predict protein function.

Proteomics and Protein Protein Interactions Book
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Proteomics and Protein Protein Interactions

  • Author : Gabriel Waksman
  • Publisher : Springer Science & Business Media
  • Release Date : 2005-12-21
  • Genre: Medical
  • Pages : 348
  • ISBN 10 : 0387245316

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The rapidly evolving field of protein science has now come to realize the ubiquity and importance of protein-protein interactions. It had been known for some time that proteins may interact with each other to form functional complexes, but it was thought to be the property of only a handful of key proteins. However, with the advent of high throughput proteomics to monitor protein-protein interactions at an organism level, we can now safely state that protein-protein interactions are the norm and not the exception. Thus, protein function must be understood in the larger context of the various binding complexes that each protein may form with interacting partners at a given time in the life cycle of a cell. Proteins are now seen as forming sophisticated interaction networks subject to remarkable regulation. The study of these interaction networks and regulatory mechanism, which I would like to term "systems proteomics," is one of the thriving fields of proteomics. The bird-eye view that systems proteomics offers should not however mask the fact that proteins are each characterized by a unique set of physical and chemical properties. In other words, no protein looks and behaves like another. This complicates enormously the design of high-throughput proteomics methods. Unlike genes, which, by and large, display similar physico-chemical behaviors and thus can be easily used in a high throughput mode, proteins are not easily amenable to the same treatment. It is thus important to remind researchers active in the proteomics field the fundamental basis of protein chemistry. This book attempts to bridge the two extreme ends of protein science: on one end, systems proteomics, which describes, at a system level, the intricate connection network that proteins form in a cell, and on the other end, protein chemistry and biophysics, which describe the molecular properties of individual proteins and the structural and thermodynamic basis of their interactions within the network. Br

Protein Protein Interaction Networks Book

Protein Protein Interaction Networks

  • Author : Stefan Canzar
  • Publisher : Unknown
  • Release Date : 2019
  • Genre: Electronic books
  • Pages : 286
  • ISBN 10 : 1493998730

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This volume explores techniques that study interactions between proteins in different species, and combines them with context-specific data, analysis of omics datasets, and assembles individual interactions into higher-order semantic units, i.e., protein complexes and functional modules. The chapters in this book cover computational methods that solve diverse tasks such as the prediction of functional protein-protein interactions; the alignment-based comparison of interaction networks by SANA; using the RaptorX-ComplexContact webserver to predict inter-protein residue-residue contacts; the docking of alternative confirmations of proteins participating in binary interactions and the visually-guided selection of a docking model using COZOID; the detection of novel functional units by KeyPathwayMiner and how PathClass can use such de novo pathways to classify breast cancer subtypes. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary hardware- and software, step-by-step, readily reproducible computational protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and comprehensive, Protein-Protein Interaction Networks: Methods and Protocols is a valuable resource for both novice and expert researchers who are interested in learning more about this evolving field.

ProteinProtein Interaction Regulators Book

ProteinProtein Interaction Regulators

  • Author : Siddhartha Roy
  • Publisher : Royal Society of Chemistry
  • Release Date : 2020-12-17
  • Genre: Science
  • Pages : 380
  • ISBN 10 : 9781839160509

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New genomic information has revealed the crucial role that protein–protein interactions (PPIs) play in regulating numerous cellular functions. Aberrant forms of these interactions are common in numerous diseases and thus PPIs have emerged as a vast class of critical drug targets. Despite the importance of PPIs in biology, it has been extremely challenging to convert targets into therapeutics and targeting PPIs had long been considered a very difficult task. However, over the past decade the field has advanced with increasing growth in the number of successful PPI regulators. Protein–Protein Interaction Regulators surveys the latest advances in the structural understanding of PPIs as well as recent developments in modulator discovery.