Patterns In Big Data Bioinformatics

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Big Data Analytics in Bioinformatics and Healthcare

Author : Wang, Baoying
Publisher : IGI Global
ISBN 13 : 1466666129
Total Pages : 552 pages
Book Rating : 4.4/5 (666 download)

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Book Synopsis Big Data Analytics in Bioinformatics and Healthcare by : Wang, Baoying

Download or read book Big Data Analytics in Bioinformatics and Healthcare written by Wang, Baoying and published by IGI Global. This book was released on 2014-10-31 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: As technology evolves and electronic data becomes more complex, digital medical record management and analysis becomes a challenge. In order to discover patterns and make relevant predictions based on large data sets, researchers and medical professionals must find new methods to analyze and extract relevant health information. Big Data Analytics in Bioinformatics and Healthcare merges the fields of biology, technology, and medicine in order to present a comprehensive study on the emerging information processing applications necessary in the field of electronic medical record management. Complete with interdisciplinary research resources, this publication is an essential reference source for researchers, practitioners, and students interested in the fields of biological computation, database management, and health information technology, with a special focus on the methodologies and tools to manage massive and complex electronic information.

Pattern Discovery in Bioinformatics

Author : Laxmi Parida
Publisher : CRC Press
ISBN 13 : 1420010735
Total Pages : 512 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Pattern Discovery in Bioinformatics by : Laxmi Parida

Download or read book Pattern Discovery in Bioinformatics written by Laxmi Parida and published by CRC Press. This book was released on 2007-07-04 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: The computational methods of bioinformatics are being used more and more to process the large volume of current biological data. Promoting an understanding of the underlying biology that produces this data, Pattern Discovery in Bioinformatics: Theory and Algorithms provides the tools to study regularities in biological data. Taking a systema

Patterns in Big Data Bioinformatics

Author : Mateusz Garbulowski
Publisher :
ISBN 13 : 9789151313078
Total Pages : pages
Book Rating : 4.3/5 (13 download)

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Book Synopsis Patterns in Big Data Bioinformatics by : Mateusz Garbulowski

Download or read book Patterns in Big Data Bioinformatics written by Mateusz Garbulowski and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Big Data Analytics in Computational Biology and Bioinformatics

Author : Kevin Byron
Publisher :
ISBN 13 :
Total Pages : 100 pages
Book Rating : 4.:/5 (122 download)

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Book Synopsis Big Data Analytics in Computational Biology and Bioinformatics by : Kevin Byron

Download or read book Big Data Analytics in Computational Biology and Bioinformatics written by Kevin Byron and published by . This book was released on 2017 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data analytics in computational biology and bioinformatics refers to an array of operations including biological pattern discovery, classification, prediction, inference, clustering as well as data mining in the cloud, among others. This dissertation addresses big data analytics by investigating two important operations, namely pattern discovery and network inference.

Pattern Recognition And Big Data

Author : Sankar Kumar Pal
Publisher : World Scientific
ISBN 13 : 9813144564
Total Pages : 875 pages
Book Rating : 4.8/5 (131 download)

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Book Synopsis Pattern Recognition And Big Data by : Sankar Kumar Pal

Download or read book Pattern Recognition And Big Data written by Sankar Kumar Pal and published by World Scientific. This book was released on 2016-12-15 with total page 875 pages. Available in PDF, EPUB and Kindle. Book excerpt: Containing twenty six contributions by experts from all over the world, this book presents both research and review material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, linguistic, fuzzy-set-theoretic, neural, evolutionary computing and rough-set-theoretic to hybrid soft computing, with significant real-life applications.Pattern Recognition and Big Data provides state-of-the-art classical and modern approaches to pattern recognition and mining, with extensive real life applications. The book describes efficient soft and robust machine learning algorithms and granular computing techniques for data mining and knowledge discovery; and the issues associated with handling Big Data. Application domains considered include bioinformatics, cognitive machines (or machine mind developments), biometrics, computer vision, the e-nose, remote sensing and social network analysis.

Bioinformatics and Medical Applications

Author : A. Suresh
Publisher : John Wiley & Sons
ISBN 13 : 1119791839
Total Pages : 356 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Bioinformatics and Medical Applications by : A. Suresh

Download or read book Bioinformatics and Medical Applications written by A. Suresh and published by John Wiley & Sons. This book was released on 2022-04-12 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: BIOINFORMATICS AND MEDICAL APPLICATIONS The main topics addressed in this book are big data analytics problems in bioinformatics research such as microarray data analysis, sequence analysis, genomics-based analytics, disease network analysis, techniques for big data analytics, and health information technology. Bioinformatics and Medical Applications: Big Data Using Deep Learning Algorithms analyses massive biological datasets using computational approaches and the latest cutting-edge technologies to capture and interpret biological data. The book delivers various bioinformatics computational methods used to identify diseases at an early stage by assembling cutting-edge resources into a single collection designed to enlighten the reader on topics focusing on computer science, mathematics, and biology. In modern biology and medicine, bioinformatics is critical for data management. This book explains the bioinformatician’s important tools and examines how they are used to evaluate biological data and advance disease knowledge. The editors have curated a distinguished group of perceptive and concise chapters that presents the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to healthcare. Applying deep learning techniques for data-driven solutions in health information allows automated analysis whose method can be more advantageous in supporting the problems arising from medical and health-related information. Audience The primary audience for the book includes specialists, researchers, postgraduates, designers, experts, and engineers, who are occupied with biometric research and security-related issues.

Computational Intelligence and Big Data Analytics

Author : Ch. Satyanarayana
Publisher : Springer
ISBN 13 : 9811305447
Total Pages : 137 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Computational Intelligence and Big Data Analytics by : Ch. Satyanarayana

Download or read book Computational Intelligence and Big Data Analytics written by Ch. Satyanarayana and published by Springer. This book was released on 2018-09-08 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights major issues related to big data analysis using computational intelligence techniques, mostly interdisciplinary in nature. It comprises chapters on computational intelligence technologies, such as neural networks and learning algorithms, evolutionary computation, fuzzy systems and other emerging techniques in data science and big data, ranging from methodologies, theory and algorithms for handling big data, to their applications in bioinformatics and related disciplines. The book describes the latest solutions, scientific results and methods in solving intriguing problems in the fields of big data analytics, intelligent agents and computational intelligence. It reflects the state of the art research in the field and novel applications of new processing techniques in computer science. This book is useful to both doctoral students and researchers from computer science and engineering fields and bioinformatics related domains.

ADVANCES IN BIOINFORMATICS AND BIG DATA ANALYTICS.

Author : SUJATA. DASH
Publisher :
ISBN 13 : 9789798886973
Total Pages : 0 pages
Book Rating : 4.8/5 (869 download)

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Book Synopsis ADVANCES IN BIOINFORMATICS AND BIG DATA ANALYTICS. by : SUJATA. DASH

Download or read book ADVANCES IN BIOINFORMATICS AND BIG DATA ANALYTICS. written by SUJATA. DASH and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Association Analysis Techniques and Applications in Bioinformatics

Author : Qingfeng Chen
Publisher : Springer Nature
ISBN 13 : 9819982510
Total Pages : 396 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Association Analysis Techniques and Applications in Bioinformatics by : Qingfeng Chen

Download or read book Association Analysis Techniques and Applications in Bioinformatics written by Qingfeng Chen and published by Springer Nature. This book was released on with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Applying Big Data Analytics in Bioinformatics and Medicine

Author : Lytras, Miltiadis D.
Publisher : IGI Global
ISBN 13 : 1522526080
Total Pages : 492 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Applying Big Data Analytics in Bioinformatics and Medicine by : Lytras, Miltiadis D.

Download or read book Applying Big Data Analytics in Bioinformatics and Medicine written by Lytras, Miltiadis D. and published by IGI Global. This book was released on 2017-06-16 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many aspects of modern life have become personalized, yet healthcare practices have been lagging behind in this trend. It is now becoming more common to use big data analysis to improve current healthcare and medicinal systems, and offer better health services to all citizens. Applying Big Data Analytics in Bioinformatics and Medicine is a comprehensive reference source that overviews the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to the healthcare field. Featuring coverage on relevant topics that include smart data, proteomics, medical data storage, and drug design, this publication is an ideal resource for medical professionals, healthcare practitioners, academicians, and researchers interested in the latest trends and techniques in personalized medicine.

Sequence Data Mining

Author : Guozhu Dong
Publisher : Springer Science & Business Media
ISBN 13 : 0387699376
Total Pages : 160 pages
Book Rating : 4.3/5 (876 download)

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Book Synopsis Sequence Data Mining by : Guozhu Dong

Download or read book Sequence Data Mining written by Guozhu Dong and published by Springer Science & Business Media. This book was released on 2007-10-31 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding sequence data, and the ability to utilize this hidden knowledge, will create a significant impact on many aspects of our society. Examples of sequence data include DNA, protein, customer purchase history, web surfing history, and more. This book provides thorough coverage of the existing results on sequence data mining as well as pattern types and associated pattern mining methods. It offers balanced coverage on data mining and sequence data analysis, allowing readers to access the state-of-the-art results in one place.

Gene Expression Data Analysis

Author : Pankaj Barah
Publisher : CRC Press
ISBN 13 : 1000425738
Total Pages : 379 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Gene Expression Data Analysis by : Pankaj Barah

Download or read book Gene Expression Data Analysis written by Pankaj Barah and published by CRC Press. This book was released on 2021-11-21 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: Development of high-throughput technologies in molecular biology during the last two decades has contributed to the production of tremendous amounts of data. Microarray and RNA sequencing are two such widely used high-throughput technologies for simultaneously monitoring the expression patterns of thousands of genes. Data produced from such experiments are voluminous (both in dimensionality and numbers of instances) and evolving in nature. Analysis of huge amounts of data toward the identification of interesting patterns that are relevant for a given biological question requires high-performance computational infrastructure as well as efficient machine learning algorithms. Cross-communication of ideas between biologists and computer scientists remains a big challenge. Gene Expression Data Analysis: A Statistical and Machine Learning Perspective has been written with a multidisciplinary audience in mind. The book discusses gene expression data analysis from molecular biology, machine learning, and statistical perspectives. Readers will be able to acquire both theoretical and practical knowledge of methods for identifying novel patterns of high biological significance. To measure the effectiveness of such algorithms, we discuss statistical and biological performance metrics that can be used in real life or in a simulated environment. This book discusses a large number of benchmark algorithms, tools, systems, and repositories that are commonly used in analyzing gene expression data and validating results. This book will benefit students, researchers, and practitioners in biology, medicine, and computer science by enabling them to acquire in-depth knowledge in statistical and machine-learning-based methods for analyzing gene expression data. Key Features: An introduction to the Central Dogma of molecular biology and information flow in biological systems A systematic overview of the methods for generating gene expression data Background knowledge on statistical modeling and machine learning techniques Detailed methodology of analyzing gene expression data with an example case study Clustering methods for finding co-expression patterns from microarray, bulkRNA, and scRNA data A large number of practical tools, systems, and repositories that are useful for computational biologists to create, analyze, and validate biologically relevant gene expression patterns Suitable for multidisciplinary researchers and practitioners in computer science and biological sciences

Granular Neural Networks, Pattern Recognition and Bioinformatics

Author : Sankar K. Pal
Publisher : Springer
ISBN 13 : 331957115X
Total Pages : 241 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Granular Neural Networks, Pattern Recognition and Bioinformatics by : Sankar K. Pal

Download or read book Granular Neural Networks, Pattern Recognition and Bioinformatics written by Sankar K. Pal and published by Springer. This book was released on 2017-05-02 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a uniform framework describing how fuzzy rough granular neural network technologies can be formulated and used in building efficient pattern recognition and mining models. It also discusses the formation of granules in the notion of both fuzzy and rough sets. Judicious integration in forming fuzzy-rough information granules based on lower approximate regions enables the network to determine the exactness in class shape as well as to handle the uncertainties arising from overlapping regions, resulting in efficient and speedy learning with enhanced performance. Layered network and self-organizing analysis maps, which have a strong potential in big data, are considered as basic modules,. The book is structured according to the major phases of a pattern recognition system (e.g., classification, clustering, and feature selection) with a balanced mixture of theory, algorithm, and application. It covers the latest findings as well as directions for future research, particularly highlighting bioinformatics applications. The book is recommended for both students and practitioners working in computer science, electrical engineering, data science, system design, pattern recognition, image analysis, neural computing, social network analysis, big data analytics, computational biology and soft computing.

Scalable Pattern Recognition Algorithms

Author : Pradipta Maji
Publisher : Springer Science & Business Media
ISBN 13 : 3319056301
Total Pages : 316 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Scalable Pattern Recognition Algorithms by : Pradipta Maji

Download or read book Scalable Pattern Recognition Algorithms written by Pradipta Maji and published by Springer Science & Business Media. This book was released on 2014-03-19 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the need for a unified framework describing how soft computing and machine learning techniques can be judiciously formulated and used in building efficient pattern recognition models. The text reviews both established and cutting-edge research, providing a careful balance of theory, algorithms, and applications, with a particular emphasis given to applications in computational biology and bioinformatics. Features: integrates different soft computing and machine learning methodologies with pattern recognition tasks; discusses in detail the integration of different techniques for handling uncertainties in decision-making and efficiently mining large biological datasets; presents a particular emphasis on real-life applications, such as microarray expression datasets and magnetic resonance images; includes numerous examples and experimental results to support the theoretical concepts described; concludes each chapter with directions for future research and a comprehensive bibliography.

Big Data Analysis for Bioinformatics and Biomedical Discoveries

Author : Shui Qing Ye
Publisher : CRC Press
ISBN 13 : 149872454X
Total Pages : 286 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Big Data Analysis for Bioinformatics and Biomedical Discoveries by : Shui Qing Ye

Download or read book Big Data Analysis for Bioinformatics and Biomedical Discoveries written by Shui Qing Ye and published by CRC Press. This book was released on 2016-01-13 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: Demystifies Biomedical and Biological Big Data AnalysesBig Data Analysis for Bioinformatics and Biomedical Discoveries provides a practical guide to the nuts and bolts of Big Data, enabling you to quickly and effectively harness the power of Big Data to make groundbreaking biological discoveries, carry out translational medical research, and implem

Big Data Analytics in Genomics

Author : Ka-Chun Wong
Publisher : Springer
ISBN 13 : 3319412795
Total Pages : 426 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Big Data Analytics in Genomics by : Ka-Chun Wong

Download or read book Big Data Analytics in Genomics written by Ka-Chun Wong and published by Springer. This book was released on 2016-10-24 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: This contributed volume explores the emerging intersection between big data analytics and genomics. Recent sequencing technologies have enabled high-throughput sequencing data generation for genomics resulting in several international projects which have led to massive genomic data accumulation at an unprecedented pace. To reveal novel genomic insights from this data within a reasonable time frame, traditional data analysis methods may not be sufficient or scalable, forcing the need for big data analytics to be developed for genomics. The computational methods addressed in the book are intended to tackle crucial biological questions using big data, and are appropriate for either newcomers or veterans in the field.This volume offers thirteen peer-reviewed contributions, written by international leading experts from different regions, representing Argentina, Brazil, China, France, Germany, Hong Kong, India, Japan, Spain, and the USA. In particular, the book surveys three main areas: statistical analytics, computational analytics, and cancer genome analytics. Sample topics covered include: statistical methods for integrative analysis of genomic data, computation methods for protein function prediction, and perspectives on machine learning techniques in big data mining of cancer. Self-contained and suitable for graduate students, this book is also designed for bioinformaticians, computational biologists, and researchers in communities ranging from genomics, big data, molecular genetics, data mining, biostatistics, biomedical science, cancer research, medical research, and biology to machine learning and computer science. Readers will find this volume to be an essential read for appreciating the role of big data in genomics, making this an invaluable resource for stimulating further research on the topic.

Gene Quantification

Author : Francois Ferre
Publisher : Springer Science & Business Media
ISBN 13 : 1461241642
Total Pages : 379 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Gene Quantification by : Francois Ferre

Download or read book Gene Quantification written by Francois Ferre and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geneticists and molecular biologists have been interested in quantifying genes and their products for many years and for various reasons (Bishop, 1974). Early molecular methods were based on molecular hybridization, and were devised shortly after Marmur and Doty (1961) first showed that denaturation of the double helix could be reversed - that the process of molecular reassociation was exquisitely sequence dependent. Gillespie and Spiegelman (1965) developed a way of using the method to titrate the number of copies of a probe within a target sequence in which the target sequence was fixed to a membrane support prior to hybridization with the probe - typically a RNA. Thus, this was a precursor to many of the methods still in use, and indeed under development, today. Early examples of the application of these methods included the measurement of the copy numbers in gene families such as the ribosomal genes and the immunoglo bulin family. Amplification of genes in tumors and in response to drug treatment was discovered by this method. In the same period, methods were invented for estimating gene num bers based on the kinetics of the reassociation process - the so-called Cot analysis. This method, which exploits the dependence of the rate of reassociation on the concentration of the two strands, revealed the presence of repeated sequences in the DNA of higher eukaryotes (Britten and Kohne, 1968). An adaptation to RNA, Rot analysis (Melli and Bishop, 1969), was used to measure the abundance of RNAs in a mixed population.