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Advanced Data Mining Technologies in Bioinformatics

Advanced Data Mining Technologies in Bioinformatics
Author: Hui-Huang Hsu
Publisher: IGI Global
Total Pages: 343
Release: 2006-01-01
Genre: Computers
ISBN: 1591408636

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"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.


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.


Data Mining for Bioinformatics

Data Mining for Bioinformatics
Author: Sumeet Dua
Publisher: CRC Press
Total Pages: 351
Release: 2012-11-06
Genre: Computers
ISBN: 1466588667

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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

Data Mining
Author: Sushmita Mitra
Publisher: John Wiley & Sons
Total Pages: 423
Release: 2005-01-21
Genre: Computers
ISBN: 0471474886

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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


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


Data Mining for Bioinformatics Applications

Data Mining for Bioinformatics Applications
Author: He Zengyou
Publisher: Woodhead Publishing
Total Pages: 100
Release: 2015-06-09
Genre: Computers
ISBN: 008100107X

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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


Advanced Data Mining Tools and Methods for Social Computing

Advanced Data Mining Tools and Methods for Social Computing
Author: Sourav De
Publisher: Academic Press
Total Pages: 294
Release: 2022-01-14
Genre: Computers
ISBN: 0323857094

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Advanced Data Mining Tools and Methods for Social Computing explores advances in the latest data mining tools, methods, algorithms and the architectures being developed specifically for social computing and social network analysis. The book reviews major emerging trends in technology that are supporting current advancements in social networks, including data mining techniques and tools. It also aims to highlight the advancement of conventional approaches in the field of social networking. Chapter coverage includes reviews of novel techniques and state-of-the-art advances in the area of data mining, machine learning, soft computing techniques, and their applications in the field of social network analysis. Provides insights into the latest research trends in social network analysis Covers a broad range of data mining tools and methods for social computing and analysis Includes practical examples and case studies across a range of tools and methods Features coding examples and supplementary data sets in every chapter


Biomedical Data Mining for Information Retrieval

Biomedical Data Mining for Information Retrieval
Author: Sujata Dash
Publisher: John Wiley & Sons
Total Pages: 450
Release: 2021-08-06
Genre: Computers
ISBN: 1119711266

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BIOMEDICAL DATA MINING FOR INFORMATION RETRIEVAL This book not only emphasizes traditional computational techniques, but discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. Biomedical Data Mining for Information Retrieval 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 healthcare 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 patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally. These images are mainly in the form of computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients’ biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions relating to healthcare. Image mining in medicine can help to uncover new relationships between data and reveal new useful information that can be helpful for doctors in treating their patients. Audience Researchers in various fields including computer science, medical informatics, healthcare IOT, artificial intelligence, machine learning, image processing, clinical big data analytics.


Computation in BioInformatics

Computation in BioInformatics
Author: S. Balamurugan
Publisher: John Wiley & Sons
Total Pages: 354
Release: 2021-10-19
Genre: Computers
ISBN: 1119654718

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COMPUTATION IN BIOINFORMATICS Bioinformatics is a platform between the biology and information technology and this book provides readers with an understanding of the use of bioinformatics tools in new drug design. The discovery of new solutions to pandemics is facilitated through the use of promising bioinformatics techniques and integrated approaches. This book covers a broad spectrum of the bioinformatics field, starting with the basic principles, concepts, and application areas. Also covered is the role of bioinformatics in drug design and discovery, including aspects of molecular modeling. Some of the chapters provide detailed information on bioinformatics related topics, such as silicon design, protein modeling, DNA microarray analysis, DNA-RNA barcoding, and gene sequencing, all of which are currently needed in the industry. Also included are specialized topics, such as bioinformatics in cancer detection, genomics, and proteomics. Moreover, a few chapters explain highly advanced topics, like machine learning and covalent approaches to drug design and discovery, all of which are significant in pharma and biotech research and development. Audience Researchers and engineers in computation biology, information technology, bioinformatics, drug design, biotechnology, pharmaceutical sciences.


Introduction to Data Mining for the Life Sciences

Introduction to Data Mining for the Life Sciences
Author: Rob Sullivan
Publisher: Springer Science & Business Media
Total Pages: 644
Release: 2012-01-07
Genre: Science
ISBN: 1597452904

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Data mining provides a set of new techniques to integrate, synthesize, and analyze tdata, uncovering the hidden patterns that exist within. Traditionally, techniques such as kernel learning methods, pattern recognition, and data mining, have been the domain of researchers in areas such as artificial intelligence, but leveraging these tools, techniques, and concepts against your data asset to identify problems early, understand interactions that exist and highlight previously unrealized relationships through the combination of these different disciplines can provide significant value for the investigator and her organization.