Data Mining for Bioinformatics Applications

Data Mining for Bioinformatics Applications provides valuable information on the data mining methods have been widely used for solving real bioinformatics problems, including problem definition, data collection, data preprocessing, modeling, and validation. The text uses an example-based method to illustrate how to apply data mining techniques to solve real bioinformatics problems, containing 45 bioinformatics problems that have been investigated in recent research. For each example, the entire data mining process is described, ranging from data preprocessing to modeling and result validation. Provides valuable information on the data mining methods have been widely used for solving real bioinformatics problems Uses an example-based method to illustrate how to apply data mining techniques to solve real bioinformatics problems Contains 45 bioinformatics problems that have been investigated in recent research

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  • Author : He Zengyou
  • Publisher : Woodhead Publishing
  • Pages : 100 pages
  • ISBN : 008100107X
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKData Mining for Bioinformatics Applications

Data Mining for Bioinformatics Applications

Data Mining for Bioinformatics Applications
  • Author : He Zengyou
  • Publisher : Woodhead Publishing
  • Release : 09 June 2015
GET THIS BOOKData Mining for Bioinformatics Applications

Data Mining for Bioinformatics Applications provides valuable information on the data mining methods have been widely used for solving real bioinformatics problems, including problem definition, data collection, data preprocessing, modeling, and validation. The text uses an example-based method to illustrate how to apply data mining techniques to solve real bioinformatics problems, containing 45 bioinformatics problems that have been investigated in recent research. For each example, the entire data mining process is described, ranging from data preprocessing to modeling and result validation.

Data Mining for Bioinformatics

Data Mining for Bioinformatics
  • Author : Sumeet Dua,Pradeep Chowriappa
  • Publisher : CRC Press
  • Release : 06 November 2012
GET THIS BOOKData Mining for Bioinformatics

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,

Data Mining in Bioinformatics

Data Mining in Bioinformatics
  • Author : Jason T. L. Wang,Mohammed J. Zaki,Hannu Toivonen,Dennis Shasha
  • Publisher : Springer Science & Business Media
  • Release : 30 March 2006
GET THIS BOOKData Mining in Bioinformatics

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.

Multiobjective Genetic Algorithms for Clustering

Multiobjective Genetic Algorithms for Clustering
  • Author : Ujjwal Maulik,Sanghamitra Bandyopadhyay,Anirban Mukhopadhyay
  • Publisher : Springer Science & Business Media
  • Release : 01 September 2011
GET THIS BOOKMultiobjective Genetic Algorithms for Clustering

This is the first book primarily dedicated to clustering using multiobjective genetic algorithms with extensive real-life applications in data mining and bioinformatics. The authors first offer detailed introductions to the relevant techniques – genetic algorithms, multiobjective optimization, soft computing, data mining and bioinformatics. They then demonstrate systematic applications of these techniques to real-world problems in the areas of data mining, bioinformatics and geoscience. The authors offer detailed theoretical and statistical notes, guides to future research, and chapter summaries. The book can

Handbook of Statistical Analysis and Data Mining Applications

Handbook of Statistical Analysis and Data Mining Applications
  • Author : Robert Nisbet,Gary Miner,Ken Yale
  • Publisher : Elsevier
  • Release : 09 November 2017
GET THIS BOOKHandbook of Statistical Analysis and Data Mining Applications

Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and

Biological Data Mining and Its Applications in Healthcare

Biological Data Mining and Its Applications in Healthcare
  • Author : Xiaoli Li,See-Kiong Ng,Jason T L Wang
  • Publisher : World Scientific
  • Release : 28 November 2013
GET THIS BOOKBiological Data Mining and Its Applications in Healthcare

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

Contrast Data Mining

Contrast Data Mining
  • Author : Guozhu Dong,James Bailey
  • Publisher : CRC Press
  • Release : 19 April 2016
GET THIS BOOKContrast Data Mining

A Fruitful Field for Researching Data Mining Methodology and for Solving Real-Life Problems Contrast Data Mining: Concepts, Algorithms, and Applications collects recent results from this specialized area of data mining that have previously been scattered in the literature, making them more accessible to researchers and developers in data mining and other fields. The book not only presents concepts and techniques for contrast data mining, but also explores the use of contrast mining to solve challenging problems in various scientific, medical,

Knowledge Discovery in Bioinformatics

Knowledge Discovery in Bioinformatics
  • Author : Xiaohua Hu,Yi Pan
  • Publisher : John Wiley & Sons
  • Release : 11 June 2007
GET THIS BOOKKnowledge Discovery in Bioinformatics

The purpose of this edited book is to bring together the ideas and findings of data mining researchers and bioinformaticians by discussing cutting-edge research topics such as, gene expressions, protein/RNA structure prediction, phylogenetics, sequence and structural motifs, genomics and proteomics, gene findings, drug design, RNAi and microRNA analysis, text mining in bioinformatics, modelling of biochemical pathways, biomedical ontologies, system biology and pathways, and biological database management.

Biomedical Data Mining for Information Retrieval

Biomedical Data Mining for Information Retrieval
  • Author : Subhendu Kumar Pani,Sujata Dash,S. Balamurugan,Ajith Abraham
  • Publisher : John Wiley & Sons
  • Release : 06 August 2021
GET THIS BOOKBiomedical Data Mining for Information Retrieval

This book comprehensively covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and Health Informatics is an emerging field of research at the intersection of information science, computer science, and health care and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including

Biological Data Mining

Biological Data Mining
  • Author : Jake Y. Chen,Stefano Lonardi
  • Publisher : CRC Press
  • Release : 01 September 2009
GET THIS BOOKBiological Data Mining

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 interdisciplinary data mining researchers who cover state-of-the-art biological topics. The first section of the book discusses challenges and opportunities in analyzing and mining biological sequences and structures to gain insight into molecular functions. The

Data Mining in Biomedicine

Data Mining in Biomedicine
  • Author : Panos M. Pardalos,Vladimir L. Boginski,Alkis Vazacopoulos
  • Publisher : Springer Science & Business Media
  • Release : 10 December 2008
GET THIS BOOKData Mining in Biomedicine

This volume presents an extensive collection of contributions covering aspects of the exciting and important research field of data mining techniques in biomedicine. Coverage includes new approaches for the analysis of biomedical data; applications of data mining techniques to real-life problems in medical practice; comprehensive reviews of recent trends in the field. The book addresses incorporation of data mining in fundamental areas of biomedical research: genomics, proteomics, protein characterization, and neuroscience.

Computation in BioInformatics

Computation in BioInformatics
  • Author : S. Balamurugan,Anand T. Krishnan,Dinesh Goyal,Balakumar Chandrasekaran,Boomi Pandi
  • Publisher : John Wiley & Sons
  • Release : 14 December 2021
GET THIS BOOKComputation in BioInformatics

Bioinformatics is a platform between the biology and information technology. The book covers a broad spectrum of the bioinformatics fields starting from the basic principles, concepts, and multidisciplinary application areas. It comprises a collection of chapters describing the role of bioinformatics in drug design and discovery including the molecular modeling aspects; chapters detailing topics such as silico design, protein modeling, DNA Microarray Analysis, DNA-RNA barcoding, gene sequencing; specialized topics such as bioinformatics in cancer detection, genomics, proteomics, machine learning, covalent

Data Mining for Scientific and Engineering Applications

Data Mining for Scientific and Engineering Applications
  • Author : R.L. Grossman,C. Kamath,P. Kegelmeyer,V. Kumar,R. Namburu
  • Publisher : Springer Science & Business Media
  • Release : 01 December 2013
GET THIS BOOKData Mining for Scientific and Engineering Applications

Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well