Fundamentals of Data Mining in Genomics and Proteomics PDF Download

Author: Werner Dubitzky
Publisher: Springer Science & Business Media
ISBN: 0387475095
Category : Science
Languages : en
Pages : 300

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Book Description
This book presents state-of-the-art analytical methods from statistics and data mining for the analysis of high-throughput data from genomics and proteomics. It adopts an approach focusing on concepts and applications and presents key analytical techniques for the analysis of genomics and proteomics data by detailing their underlying principles, merits and limitations.

Author: Darius M. Dziuda
Publisher: John Wiley & Sons
ISBN: 0470593407
Category : Computers
Languages : en
Pages : 348

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Book Description
Data Mining for Genomics and Proteomics uses pragmatic examples and a complete case study to demonstrate step-by-step how biomedical studies can be used to maximize the chance of extracting new and useful biomedical knowledge from data. It is an excellent resource for students and professionals involved with gene or protein expression data in a variety of settings.

Author: Hui-Huang Hsu
Publisher: IGI Global
ISBN: 1591408636
Category : Computers
Languages : en
Pages : 343

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Book Description
"This book covers research topics of data mining on bioinformatics presenting the basics and problems of bioinformatics and applications of data mining technologies pertaining to the field"--Provided by publisher.

Author: Hiroshi Mamitsuka
Publisher: Humana
ISBN: 9781493993260
Category : Science
Languages : en
Pages : 243

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Book Description
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.

Author: Li, Xiao-Li
Publisher: IGI Global
ISBN: 1605663999
Category : Technology & Engineering
Languages : en
Pages : 448

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Book Description
"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.

Author: Samantha Fowler
Publisher:
ISBN: 9781739015503
Category :
Languages : en
Pages : 0

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Book Description
Black & white print. Concepts of Biology is designed for the typical introductory biology course for nonmajors, covering standard scope and sequence requirements. The text includes interesting applications and conveys the major themes of biology, with content that is meaningful and easy to understand. The book is designed to demonstrate biology concepts and to promote scientific literacy.

Author: N Saraswathy
Publisher: Elsevier
ISBN: 1908818050
Category : Science
Languages : en
Pages : 271

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Book Description
Concepts and techniques in genomics and proteomics covers the important concepts of high-throughput modern techniques used in the genomics and proteomics field. Each technique is explained with its underlying concepts, and simple line diagrams and flow charts are included to aid understanding and memory. A summary of key points precedes each chapter within the book, followed by detailed description in the subsections. Each subsection concludes with suggested relevant original references. - Provides definitions for key concepts - Case studies are included to illustrate ideas - Important points to remember are noted

Author: Jake Y. Chen
Publisher: CRC Press
ISBN: 1420086855
Category : Computers
Languages : en
Pages : 736

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Book Description
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

Author: Jason T. L. Wang
Publisher: Springer Science & Business Media
ISBN: 9781852336714
Category : Computers
Languages : en
Pages : 356

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Book Description
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.

Author: Sumeet Dua
Publisher: CRC Press
ISBN: 0849328012
Category : Computers
Languages : en
Pages : 351

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Book Description
Covering theory, algorithms, and methodologies, as well as data mining technologies, Data Mining for Bioinformatics provides a comprehensive discussion of data-intensive computations used in data mining with applications in bioinformatics. It supplies a broad, yet in-depth, overview of the application domains of data mining for bioinformatics to help readers from both biology and computer science backgrounds gain an enhanced understanding of this cross-disciplinary field. The book offers authoritative coverage of data mining techniques, technologies, and frameworks used for storing, analyzing, and extracting knowledge from large databases in the bioinformatics domains, including genomics and proteomics. It begins by describing the evolution of bioinformatics and highlighting the challenges that can be addressed using data mining techniques. Introducing the various data mining techniques that can be employed in biological databases, the text is organized into four sections: Supplies a complete overview of the evolution of the field and its intersection with computational learning Describes the role of data mining in analyzing large biological databases—explaining the breath of the various feature selection and feature extraction techniques that data mining has to offer Focuses on concepts of unsupervised learning using clustering techniques and its application to large biological data Covers supervised learning using classification techniques most commonly used in bioinformatics—addressing the need for validation and benchmarking of inferences derived using either clustering or classification The book describes the various biological databases prominently referred to in bioinformatics and includes a detailed list of the applications of advanced clustering algorithms used in bioinformatics. Highlighting the challenges encountered during the application of classification on biological databases, it considers systems of both single and ensemble classifiers and shares effort-saving tips for model selection and performance estimation strategies.