Unsupervised Feature Extraction Applied To Bioinformatics

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Unsupervised Feature Extraction Applied to Bioinformatics

Author : Y-h. Taguchi
Publisher : Springer Nature
ISBN 13 : 3030224562
Total Pages : 321 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Unsupervised Feature Extraction Applied to Bioinformatics by : Y-h. Taguchi

Download or read book Unsupervised Feature Extraction Applied to Bioinformatics written by Y-h. Taguchi and published by Springer Nature. This book was released on 2019-08-23 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book proposes applications of tensor decomposition to unsupervised feature extraction and feature selection. The author posits that although supervised methods including deep learning have become popular, unsupervised methods have their own advantages. He argues that this is the case because unsupervised methods are easy to learn since tensor decomposition is a conventional linear methodology. This book starts from very basic linear algebra and reaches the cutting edge methodologies applied to difficult situations when there are many features (variables) while only small number of samples are available. The author includes advanced descriptions about tensor decomposition including Tucker decomposition using high order singular value decomposition as well as higher order orthogonal iteration, and train tenor decomposition. The author concludes by showing unsupervised methods and their application to a wide range of topics. Allows readers to analyze data sets with small samples and many features; Provides a fast algorithm, based upon linear algebra, to analyze big data; Includes several applications to multi-view data analyses, with a focus on bioinformatics.

Application Of Omics, Ai And Blockchain In Bioinformatics Research

Author : Jeffrey J P Tsai
Publisher : World Scientific
ISBN 13 : 9811203598
Total Pages : 207 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Application Of Omics, Ai And Blockchain In Bioinformatics Research by : Jeffrey J P Tsai

Download or read book Application Of Omics, Ai And Blockchain In Bioinformatics Research written by Jeffrey J P Tsai and published by World Scientific. This book was released on 2019-10-14 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the increasing availability of omics data and mounting evidence of the usefulness of computational approaches to tackle multi-level data problems in bioinformatics and biomedical research in this post-genomics era, computational biology has been playing an increasingly important role in paving the way as basis for patient-centric healthcare.Two such areas are: (i) implementing AI algorithms supported by biomedical data would deliver significant benefits/improvements towards the goals of precision medicine (ii) blockchain technology will enable medical doctors to securely and privately build personal healthcare records, and identify the right therapeutic treatments and predict the progression of the diseases.A follow-up in the publication of our book Computation Methods with Applications in Bioinformatics Analysis (2017), topics in this volume include: clinical bioinformatics, omics-based data analysis, Artificial Intelligence (AI), blockchain, big data analytics, drug discovery, RNA-seq analysis, tensor decomposition and Boolean network.

Computational Methods With Applications In Bioinformatics Analysis

Author : Tsai Jeffrey J P
Publisher : World Scientific
ISBN 13 : 981320799X
Total Pages : 232 pages
Book Rating : 4.8/5 (132 download)

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Book Synopsis Computational Methods With Applications In Bioinformatics Analysis by : Tsai Jeffrey J P

Download or read book Computational Methods With Applications In Bioinformatics Analysis written by Tsai Jeffrey J P and published by World Scientific. This book was released on 2017-06-09 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: This compendium contains 10 chapters written by world renowned researchers with expertise in semantic computing, genome sequence analysis, biomolecular interaction, time-series microarray analysis, and machine learning algorithms. The salient feature of this book is that it highlights eight types of computational techniques to tackle different biomedical applications. These techniques include unsupervised learning algorithms, principal component analysis, fuzzy integral, graph-based ensemble clustering method, semantic analysis, interolog approach, molecular simulations and enzyme kinetics. The unique volume will be a useful reference material and an inspirational read for advanced undergraduate and graduate students, computer scientists, computational biologists, bioinformatics and biomedical professionals.

Intelligent Computing Theories and Application

Author : De-Shuang Huang
Publisher : Springer
ISBN 13 : 3030267636
Total Pages : 802 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Intelligent Computing Theories and Application by : De-Shuang Huang

Download or read book Intelligent Computing Theories and Application written by De-Shuang Huang and published by Springer. This book was released on 2019-07-30 with total page 802 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set of LNCS 11643 and LNCS 11644 constitutes - in conjunction with the volume LNAI 11645 - the refereed proceedings of the 15th International Conference on Intelligent Computing, ICIC 2019, held in Nanchang, China, in August 2019. The 217 full papers of the three proceedings volumes were carefully reviewed and selected from 609 submissions. The ICIC theme unifies the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. The theme for this conference is “Advanced Intelligent Computing Methodologies and Applications.” Papers related to this theme are especially solicited, including theories, methodologies, and applications in science and technology.

Intelligent Systems for Genome Functional Annotations

Author : Shandar Ahmad
Publisher : Frontiers Media SA
ISBN 13 : 2889660907
Total Pages : 103 pages
Book Rating : 4.8/5 (896 download)

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Book Synopsis Intelligent Systems for Genome Functional Annotations by : Shandar Ahmad

Download or read book Intelligent Systems for Genome Functional Annotations written by Shandar Ahmad and published by Frontiers Media SA. This book was released on 2020-10-23 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.

Regulatory microRNA

Author : Y-h. Taguchi
Publisher : MDPI
ISBN 13 : 3038977683
Total Pages : 348 pages
Book Rating : 4.0/5 (389 download)

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Book Synopsis Regulatory microRNA by : Y-h. Taguchi

Download or read book Regulatory microRNA written by Y-h. Taguchi and published by MDPI. This book was released on 2019-04-16 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes updated information about microRNA regulation, for example, in the fields of circular RNAs, multiomics analysis, biomarkers and oncogenes. The variety of topics included in this book reaffirms the extent to which microRNA regulation affects biological processes. Although microRNAs are not translated to proteins, their importance for biological processes is not less than proteins. An understanding of their roles in various biological processes is critical to understanding gene function in these biological processes. Although non-coding RNAs other than microRNAs have recently come under investigation, microRNA still remains the front runner as the subject of genetic and biological studies. In reading the collection of papers, readers can grasp the most updated information regarding microRNA regulation, which will continue to be an important topic in genetics and biology.

Feature Extraction

Author : Isabelle Guyon
Publisher : Springer
ISBN 13 : 3540354883
Total Pages : 778 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Feature Extraction by : Isabelle Guyon

Download or read book Feature Extraction written by Isabelle Guyon and published by Springer. This book was released on 2008-11-16 with total page 778 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is both a reference for engineers and scientists and a teaching resource, featuring tutorial chapters and research papers on feature extraction. Until now there has been insufficient consideration of feature selection algorithms, no unified presentation of leading methods, and no systematic comparisons.

Handbook of Machine Learning Applications for Genomics

Author : Sanjiban Sekhar Roy
Publisher : Springer Nature
ISBN 13 : 9811691584
Total Pages : 222 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Handbook of Machine Learning Applications for Genomics by : Sanjiban Sekhar Roy

Download or read book Handbook of Machine Learning Applications for Genomics written by Sanjiban Sekhar Roy and published by Springer Nature. This book was released on 2022-06-23 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Currently, machine learning is playing a pivotal role in the progress of genomics. The applications of machine learning are helping all to understand the emerging trends and the future scope of genomics. This book provides comprehensive coverage of machine learning applications such as DNN, CNN, and RNN, for predicting the sequence of DNA and RNA binding proteins, expression of the gene, and splicing control. In addition, the book addresses the effect of multiomics data analysis of cancers using tensor decomposition, machine learning techniques for protein engineering, CNN applications on genomics, challenges of long noncoding RNAs in human disease diagnosis, and how machine learning can be used as a tool to shape the future of medicine. More importantly, it gives a comparative analysis and validates the outcomes of machine learning methods on genomic data to the functional laboratory tests or by formal clinical assessment. The topics of this book will cater interest to academicians, practitioners working in the field of functional genomics, and machine learning. Also, this book shall guide comprehensively the graduate, postgraduates, and Ph.D. scholars working in these fields.

Blockchain Applications for Healthcare Informatics

Author : Sudeep Tanwar
Publisher : Academic Press
ISBN 13 : 0323908292
Total Pages : 530 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Blockchain Applications for Healthcare Informatics by : Sudeep Tanwar

Download or read book Blockchain Applications for Healthcare Informatics written by Sudeep Tanwar and published by Academic Press. This book was released on 2022-05-20 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: Blockchain Applications for Healthcare Informatics: Beyond 5G offers a comprehensive survey of 5G-enabled technology in healthcare applications. This book investigates the latest research in blockchain technologies and seeks to answer some of the practical and methodological questions surrounding privacy and security in healthcare. It explores the most promising aspects of 5G for healthcare industries, including how hospitals and healthcare systems can do better. Chapters investigate the detailed framework needed to maintain security and privacy in 5G healthcare services using blockchain technologies, along with case studies that look at various performance evaluation metrics, such as privacy preservation, scalability and healthcare legislation. Introduces the basic architecture and taxonomy of 5G-enabled blockchain technology Analyzes issues and challenges surrounding 5G-enabled blockchain-based systems in healthcare Investigates blockchain-based healthcare applications such as telemedicine, telesurgery, remote patient monitoring, networking of the Internet of Medical Things, and augmented and virtual realty tools for training in complex medical scenarios Includes case studies and real-world examples in each chapter to demonstrate the adoption of 5G-enabled blockchain technology across various healthcare domains

Applying Machine Learning for Automated Classification of Biomedical Data in Subject-Independent Settings

Author : Thuy T. Pham
Publisher : Springer
ISBN 13 : 3319986759
Total Pages : 107 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Applying Machine Learning for Automated Classification of Biomedical Data in Subject-Independent Settings by : Thuy T. Pham

Download or read book Applying Machine Learning for Automated Classification of Biomedical Data in Subject-Independent Settings written by Thuy T. Pham and published by Springer. This book was released on 2018-08-23 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes efforts to improve subject-independent automated classification techniques using a better feature extraction method and a more efficient model of classification. It evaluates three popular saliency criteria for feature selection, showing that they share common limitations, including time-consuming and subjective manual de-facto standard practice, and that existing automated efforts have been predominantly used for subject dependent setting. It then proposes a novel approach for anomaly detection, demonstrating its effectiveness and accuracy for automated classification of biomedical data, and arguing its applicability to a wider range of unsupervised machine learning applications in subject-independent settings.

Big Data Analytics in Bioinformatics and Healthcare

Author : Wang, Baoying
Publisher : IGI Global
ISBN 13 : 1466666129
Total Pages : 528 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 528 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.

Computational Methods of Feature Selection

Author : Huan Liu
Publisher : CRC Press
ISBN 13 : 9781584888796
Total Pages : 440 pages
Book Rating : 4.8/5 (887 download)

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Book Synopsis Computational Methods of Feature Selection by : Huan Liu

Download or read book Computational Methods of Feature Selection written by Huan Liu and published by CRC Press. This book was released on 2007-10-29 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to increasing demands for dimensionality reduction, research on feature selection has deeply and widely expanded into many fields, including computational statistics, pattern recognition, machine learning, data mining, and knowledge discovery. Highlighting current research issues, Computational Methods of Feature Selection introduces the basic concepts and principles, state-of-the-art algorithms, and novel applications of this tool. The book begins by exploring unsupervised, randomized, and causal feature selection. It then reports on some recent results of empowering feature selection, including active feature selection, decision-border estimate, the use of ensembles with independent probes, and incremental feature selection. This is followed by discussions of weighting and local methods, such as the ReliefF family, k-means clustering, local feature relevance, and a new interpretation of Relief. The book subsequently covers text classification, a new feature selection score, and both constraint-guided and aggressive feature selection. The final section examines applications of feature selection in bioinformatics, including feature construction as well as redundancy-, ensemble-, and penalty-based feature selection. Through a clear, concise, and coherent presentation of topics, this volume systematically covers the key concepts, underlying principles, and inventive applications of feature selection, illustrating how this powerful tool can efficiently harness massive, high-dimensional data and turn it into valuable, reliable information.

Transactions on Rough Sets XXIII

Author : James F. Peters
Publisher : Springer Nature
ISBN 13 : 3662665441
Total Pages : 513 pages
Book Rating : 4.6/5 (626 download)

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Book Synopsis Transactions on Rough Sets XXIII by : James F. Peters

Download or read book Transactions on Rough Sets XXIII written by James F. Peters and published by Springer Nature. This book was released on 2023-01-01 with total page 513 pages. Available in PDF, EPUB and Kindle. Book excerpt: The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. Volume XXIII in the series is a continuation of a number of research streams that have grown out of the seminal work of Zdzislaw Pawlak during the first decade of the 21st century.

Data Analytics in Biomedical Engineering and Healthcare

Author : Kun Chang Lee
Publisher : Academic Press
ISBN 13 : 0128193158
Total Pages : 298 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Data Analytics in Biomedical Engineering and Healthcare by : Kun Chang Lee

Download or read book Data Analytics in Biomedical Engineering and Healthcare written by Kun Chang Lee and published by Academic Press. This book was released on 2020-10-18 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analytics in Biomedical Engineering and Healthcare explores key applications using data analytics, machine learning, and deep learning in health sciences and biomedical data. The book is useful for those working with big data analytics in biomedical research, medical industries, and medical research scientists. The book covers health analytics, data science, and machine and deep learning applications for biomedical data, covering areas such as predictive health analysis, electronic health records, medical image analysis, computational drug discovery, and genome structure prediction using predictive modeling. Case studies demonstrate big data applications in healthcare using the MapReduce and Hadoop frameworks. Examines the development and application of data analytics applications in biomedical data Presents innovative classification and regression models for predicting various diseases Discusses genome structure prediction using predictive modeling Shows readers how to develop clinical decision support systems Shows researchers and specialists how to use hybrid learning for better medical diagnosis, including case studies of healthcare applications using the MapReduce and Hadoop frameworks

Data Mining in Biomedical Imaging, Signaling, and Systems

Author : Sumeet Dua
Publisher : CRC Press
ISBN 13 : 1439839395
Total Pages : 434 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Data Mining in Biomedical Imaging, Signaling, and Systems by : Sumeet Dua

Download or read book Data Mining in Biomedical Imaging, Signaling, and Systems written by Sumeet Dua and published by CRC Press. This book was released on 2016-04-19 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining can help pinpoint hidden information in medical data and accurately differentiate pathological from normal data. It can help to extract hidden features from patient groups and disease states and can aid in automated decision making. Data Mining in Biomedical Imaging, Signaling, and Systems provides an in-depth examination of the biomedi

Application of Bioinformatics in Cancers

Author : Chad Brenner
Publisher : MDPI
ISBN 13 : 3039217887
Total Pages : 418 pages
Book Rating : 4.0/5 (392 download)

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Book Synopsis Application of Bioinformatics in Cancers by : Chad Brenner

Download or read book Application of Bioinformatics in Cancers written by Chad Brenner and published by MDPI. This book was released on 2019-11-20 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection of 25 research papers comprised of 22 original articles and 3 reviews is brought together from international leaders in bioinformatics and biostatistics. The collection highlights recent computational advances that improve the ability to analyze highly complex data sets to identify factors critical to cancer biology. Novel deep learning algorithms represent an emerging and highly valuable approach for collecting, characterizing and predicting clinical outcomes data. The collection highlights several of these approaches that are likely to become the foundation of research and clinical practice in the future. In fact, many of these technologies reveal new insights about basic cancer mechanisms by integrating data sets and structures that were previously immiscible. Accordingly, the series presented here bring forward a wide range of artificial intelligence approaches and statistical methods that can be applied to imaging and genomics data sets to identify previously unrecognized features that are critical for cancer. Our hope is that these articles will serve as a foundation for future research as the field of cancer biology transitions to integrating electronic health record, imaging, genomics and other complex datasets in order to develop new strategies that improve the overall health of individual patients.

Data Analytics in Bioinformatics

Author : Rabinarayan Satpathy
Publisher : John Wiley & Sons
ISBN 13 : 111978560X
Total Pages : 433 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Data Analytics in Bioinformatics by : Rabinarayan Satpathy

Download or read book Data Analytics in Bioinformatics written by Rabinarayan Satpathy and published by John Wiley & Sons. This book was released on 2021-01-20 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.