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Biological Data Mining in Protein Interaction Networks

Biological Data Mining in Protein Interaction Networks
Author: Li, Xiao-Li
Publisher: IGI Global
Total Pages: 450
Release: 2009-05-31
Genre: Technology & Engineering
ISBN: 1605663999

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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 Mining for Systems Biology

Data Mining for Systems Biology
Author: Hiroshi Mamitsuka
Publisher: Humana
Total Pages: 243
Release: 2019-08-04
Genre: Science
ISBN: 9781493993260

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This fully updated book collects numerous data mining techniques, reflecting the acceleration and diversity of the development of data-driven approaches to the life sciences. The first half of the volume examines genomics, particularly metagenomics and epigenomics, which promise to deepen our knowledge of genes and genomes, while the second half of the book emphasizes metabolism and the metabolome as well as relevant medicine-oriented subjects. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detail and expert implementation advice that is useful for getting optimal results. Authoritative and practical, Data Mining for Systems Biology: Methods and Protocols, Second Edition serves as an ideal resource for researchers of biology and relevant fields, such as medical, pharmaceutical, and agricultural sciences, as well as for the scientists and engineers who are working on developing data-driven techniques, such as databases, data sciences, data mining, visualization systems, and machine learning or artificial intelligence that now are central to the paradigm-altering discoveries being made with a higher frequency.


Summarizing Biological Networks

Summarizing Biological Networks
Author: Sourav S. Bhowmick
Publisher: Springer
Total Pages: 146
Release: 2017-04-17
Genre: Computers
ISBN: 331954621X

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This book focuses on the data mining, systems biology, and bioinformatics computational methods that can be used to summarize biological networks. Specifically, it discusses an array of techniques related to biological network clustering, network summarization, and differential network analysis which enable readers to uncover the functional and topological organization hidden in a large biological network. The authors also examine crucial open research problems in this arena. Academics, researchers, and advanced-level students will find this book to be a comprehensive and exceptional resource for understanding computational techniques and their applications for a summary of biological networks.


Biological Data Mining And Its Applications In Healthcare

Biological Data Mining And Its Applications In Healthcare
Author: Xiaoli Li
Publisher: World Scientific
Total Pages: 437
Release: 2013-11-28
Genre: Science
ISBN: 9814551023

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Biologists are stepping up their efforts in understanding the biological processes that underlie disease pathways in the clinical contexts. This has resulted in a flood of biological and clinical data from genomic and protein sequences, DNA microarrays, protein interactions, biomedical images, to disease pathways and electronic health records. To exploit these data for discovering new knowledge that can be translated into clinical applications, there are fundamental data analysis difficulties that have to be overcome. Practical issues such as handling noisy and incomplete data, processing compute-intensive tasks, and integrating various data sources, are new challenges faced by biologists in the post-genome era. This book will cover the fundamentals of state-of-the-art data mining techniques which have been designed to handle such challenging data analysis problems, and demonstrate with real applications how biologists and clinical scientists can employ data mining to enable them to make meaningful observations and discoveries from a wide array of heterogeneous data from molecular biology to pharmaceutical and clinical domains.


Data Management of Protein Interaction Networks

Data Management of Protein Interaction Networks
Author: Mario Cannataro
Publisher: John Wiley & Sons
Total Pages: 145
Release: 2012-02-03
Genre: Computers
ISBN: 1118103734

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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.


Protein Interaction Networks

Protein Interaction Networks
Author: Aidong Zhang
Publisher:
Total Pages: 294
Release: 2014-05-14
Genre: Science
ISBN: 9780511650390

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The first full survey of statistical, topological, data-mining, and ontology-based methods for analyzing protein-protein interaction networks.


Data Mining in Bioinformatics

Data Mining in Bioinformatics
Author: Jason T. L. Wang
Publisher: Springer Science & Business Media
Total Pages: 356
Release: 2005
Genre: Computers
ISBN: 9781852336714

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Written especially for computer scientists, all necessary biology is explained. Presents new techniques on gene expression data mining, gene mapping for disease detection, and phylogenetic knowledge discovery.


Analysis of Biological Networks

Analysis of Biological Networks
Author: Björn H. Junker
Publisher: John Wiley & Sons
Total Pages: 278
Release: 2011-09-20
Genre: Computers
ISBN: 1118209915

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An introduction to biological networks and methods for their analysis Analysis of Biological Networks is the first book of its kind to provide readers with a comprehensive introduction to the structural analysis of biological networks at the interface of biology and computer science. The book begins with a brief overview of biological networks and graph theory/graph algorithms and goes on to explore: global network properties, network centralities, network motifs, network clustering, Petri nets, signal transduction and gene regulation networks, protein interaction networks, metabolic networks, phylogenetic networks, ecological networks, and correlation networks. Analysis of Biological Networks is a self-contained introduction to this important research topic, assumes no expert knowledge in computer science or biology, and is accessible to professionals and students alike. Each chapter concludes with a summary of main points and with exercises for readers to test their understanding of the material presented. Additionally, an FTP site with links to author-provided data for the book is available for deeper study. This book is suitable as a resource for researchers in computer science, biology, bioinformatics, advanced biochemistry, and the life sciences, and also serves as an ideal reference text for graduate-level courses in bioinformatics and biological research.


Biological Data Mining

Biological Data Mining
Author: Jake Y. Chen
Publisher: CRC Press
Total Pages: 736
Release: 2009-09-01
Genre: Computers
ISBN: 1420086855

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Like a data-guzzling turbo engine, advanced data mining has been powering post-genome biological studies for two decades. Reflecting this growth, Biological Data Mining presents comprehensive data mining concepts, theories, and applications in current biological and medical research. Each chapter is written by a distinguished team of interdisciplin


Clustering Challenges In Biological Networks

Clustering Challenges In Biological Networks
Author: W Art Chaovalitwongse
Publisher: World Scientific
Total Pages: 347
Release: 2009-02-11
Genre: Science
ISBN: 9814474193

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This volume presents a collection of papers dealing with various aspects of clustering in biological networks and other related problems in computational biology. It consists of two parts, with the first part containing surveys of selected topics and the second part presenting original research contributions. This book will be a valuable source of material to faculty, students, and researchers in mathematical programming, data analysis and data mining, as well as people working in bioinformatics, computer science, engineering, and applied mathematics. In addition, the book can be used as a supplement to any course in data mining or computational/systems biology.