Data Mining for Bioinformatics Applications

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

Download or Read online Data Mining for Bioinformatics Applications full in PDF, ePub and kindle. this book written by He Zengyou and published by Woodhead Publishing which was released on 09 June 2015 with total page 100 pages. We cannot guarantee that Data Mining for Bioinformatics Applications book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. 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

Data Mining for Bioinformatics Applications

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

Data Mining for Bioinformatics

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

Textbook of Machine Learning and Data Mining

Textbook of Machine Learning and Data Mining
  • Author : Hiroshi Mamitsuka
  • Publisher : Unknown
  • Release : 12 September 2018
GET THIS BOOK Textbook of Machine Learning and Data Mining

Data-driven approaches, particularly machine learning and data mining, are the main driving force of the current artificial intelligence technology. This book covers a wide variety of methods in machine learning and data mining, dividing them from a viewpoint of data types, which begin with rather simple vectors and end by graphs and also combination of different data types. This book describes standard techniques of machine learning and data mining for each data type, especially focusing on the relevance and difference

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 BOOK Multiobjective 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

Bioinformatics

Bioinformatics
  • Author : David Edwards,Jason Stajich,David Hansen
  • Publisher : Springer Science & Business Media
  • Release : 03 September 2009
GET THIS BOOK Bioinformatics

Bioinformatics is a relatively new field of research. It evolved from the requirement to process, characterize, and apply the information being produced by DNA sequencing technology. The production of DNA sequence data continues to grow exponentially. At the same time, improved bioinformatics such as faster DNA sequence search methods have been combined with increasingly powerful computer systems to process this information. Methods are being developed for the ever more detailed quantification of gene expression, providing an insight into the function

Translational Bioinformatics Applications in Healthcare

Translational Bioinformatics Applications in Healthcare
  • Author : Khalid Raza,Nilanjan Dey
  • Publisher : CRC Press
  • Release : 20 April 2021
GET THIS BOOK Translational Bioinformatics Applications in Healthcare

Translational bioinformatics (TBI) involves development of storage, analytics, and advanced computational methods to harvest knowledge from voluminous biomedical and genomic data into 4P healthcare (proactive, predictive, preventive, and participatory). Translational Bioinformatics Applications in Healthcare offers a detailed overview on concepts of TBI, biological and clinical databases, clinical informatics, and pertinent real-case applications. It further illustrates recent advancements, tools, techniques, and applications of TBI in healthcare, including Internet of Things (IoT) potential, toxin databases, medical image analysis and telemedicine applications, analytics

Multiobjective Genetic Algorithms for Clustering

Multiobjective Genetic Algorithms for Clustering
  • Author : Ujjwal Maulik,Sanghamitra Bandyopadhyay,Anirban Mukhopadhyay
  • Publisher : Springer
  • Release : 02 September 2011
GET THIS BOOK Multiobjective 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

Knowledge Discovery in Bioinformatics

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

Advances in Data Analysis

Advances in Data Analysis
  • Author : Christos H. Skiadas
  • Publisher : Springer Science & Business Media
  • Release : 25 November 2009
GET THIS BOOK Advances in Data Analysis

This unified volume is a collection of invited chapters presenting recent developments in the field of data analysis, with applications to reliability and inference, data mining, bioinformatics, lifetime data, and neural networks. The book is a useful reference for graduate students, researchers, and practitioners in statistics, mathematics, engineering, economics, social science, bioengineering, and bioscience.

Bioinformatics

Bioinformatics
  • Author : M. H. Fulekar
  • Publisher : Springer Science & Business Media
  • Release : 24 March 2009
GET THIS BOOK Bioinformatics

Bioinformatics, computational biology, is a relatively new field that applies computer science and information technology to biology. In recent years, the discipline of bioinformatics has allowed biologists to make full use of the advances in Computer sciences and Computational statistics for advancing the biological data. Researchers in life sciences generate, collect and need to analyze an increasing number of different types of scientific data, DNA, RNA and protein sequences, in-situ and microarray gene expression including 3D protein structures and biological

Data Mining for Bioinformatics

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

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 BOOK Data 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.

Data Mining and Bioinformatics

Data Mining and Bioinformatics
  • Author : Mehmet M Dalkilic
  • Publisher : Springer Science & Business Media
  • Release : 21 December 2006
GET THIS BOOK Data Mining and Bioinformatics

This book constitutes the thoroughly refereed post-proceedings of the First VLDB 2006 International Workshop on Data Mining and Bioinformatics, VDMB 2006, held in Seoul, Korea in September 2006 in conjunction with VLDB 2006. The 15 revised full papers presented together with an invited talk were carefully reviewed and selected from 30 submissions. The papers cover various topics in the areas of microarray data analysis, bioinformatics system and text retrieval, application of gene expression data, and sequence analysis.

Research and Trends in Data Mining Technologies and Applications

Research and Trends in Data Mining Technologies and Applications
  • Author : Taniar, David
  • Publisher : IGI Global
  • Release : 31 October 2006
GET THIS BOOK Research and Trends in Data Mining Technologies and Applications

Activities in data warehousing and mining are constantly emerging. Data mining methods, algorithms, online analytical processes, data mart and practical issues consistently evolve, providing a challenge for professionals in the field. Research and Trends in Data Mining Technologies and Applications focuses on the integration between the fields of data warehousing and data mining, with emphasis on the applicability to real-world problems. This book provides an international perspective, highlighting solutions to some of researchers' toughest challenges. Developments in the knowledge discovery

Data Mining

Data Mining
  • Author : Sushmita Mitra,Tinku Acharya
  • Publisher : John Wiley & Sons
  • Release : 21 January 2005
GET THIS BOOK Data Mining

First title to ever present soft computing approaches and their application in data mining, along with the traditional hard-computing approaches Addresses the principles of multimedia data compression techniques (for image, video, text) and their role in data mining Discusses principles and classical algorithms on string matching and their role in data mining