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Deep Learning Applications In Translational Bioinformatics


Deep Learning Applications In Translational Bioinformatics
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Deep Learning Applications In Translational Bioinformatics


Deep Learning Applications In Translational Bioinformatics
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Author : Khalid Raza
language : en
Publisher: Elsevier
Release Date : 2024-03-07

Deep Learning Applications In Translational Bioinformatics written by Khalid Raza and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-07 with Technology & Engineering categories.


Deep Learning Applications in Translational Bioinformatics, a new volume in the Advances in Ubiquitous Sensing Application for Healthcare series, offers a detailed overview of basic bioinformatics, deep learning, various applications of deep learning in translational bioinformatics including deep learning ensembles, deep learning in protein classification, detection of various diseases, prediction of antiviral peptides, identification of antibiotic resistance, computer aided drug design and drug formulation. This new volume helps researchers working in the field of machine learning and bioinformatics to foster future research and development in ensemble deep learning and inspire new bioinformatics applications that cannot be attained by using traditional machine learning models. - Addresses the practical application of deep learning algorithms to a wide range of bioinformatics challenges - Presents integrative and multidisciplinary approaches to ubiquitous healthcare - Includes case studies to illustrate the concepts discussed



Translational Bioinformatics In Healthcare And Medicine


Translational Bioinformatics In Healthcare And Medicine
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Author :
language : en
Publisher: Academic Press
Release Date : 2021-05-13

Translational Bioinformatics In Healthcare And Medicine written by and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-13 with Medical categories.


Translational Bioinformatics in Healthcare and Medicine offers an overview of main principles of bioinformatics, biological databases, clinical informatics, health informatics, viroinformatics and real-case applications of translational bioinformatics in healthcare. Written by experts from both technology and clinical sides, the content brings together essential knowledge to make the best of recent advancements of the field. The book discusses topics such as next generation sequence analysis, genomics in clinical care, IoT applications, blockchain technology, patient centered interoperability of EHR, health data mining, and translational bioinformatics methods for drug discovery and drug repurposing. In addition, it discusses the role of bioinformatics in cancer research and viroinformatics approaches to counter viral diseases through informatics. This is a valuable resource for bioinformaticians, clinicians, healthcare professionals, graduate students and several members of biomedical field who are interested in learning more about how bioinformatics can impact in their research and practice. - Covers recent advancements in translational bioinformatics and its healthcare applications - Discusses integrative and multidisciplinary approaches to U-healthcare systems development and management - Bridges the gap among various knowledge domains in the field, integrating both technological and clinical knowledge into practical content



Translational Bioinformatics Applications In Healthcare


Translational Bioinformatics Applications In Healthcare
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Author : Khalid Raza
language : en
Publisher: CRC Press
Release Date : 2024-10-07

Translational Bioinformatics Applications In Healthcare written by Khalid Raza and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-07 with Computers categories.


This book offers a detailed overview and concepts of translation bioinformatics (TBI), biological/clinical databases, clinical informatics, and pertinent real-case applications. It explains advancements, tools, techniques, and applications of TBI including IoT, toxin databases, medical image analysis including COVID-19 CT-images, and so forth.



Translational Bioinformatics


Translational Bioinformatics
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Author :
language : en
Publisher: Elsevier
Release Date : 2024-03-06

Translational Bioinformatics written by and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-06 with Science categories.


Translational Bioinformatics is an emerging field in the direction of biomedical research. High throughput technologies can be applied to the generated biological data to develop the vaccine and personalized medicine. This volume consists of the chapters from different stalwart of the field covering the topics such as drug development, vector engineering, vaccine development and translational genomics. Chapters covered in this volume discuss the translational research related with cancer, Alzheimer disease and cardiovascular diseases. This volume includes the chapter describing the importance of computational resources and chemoinformatics for the translational health research. How Omics studies are helping to translate the laboratory data into the development of tools which are beneficial in the clinics have been described. How translational bioinformatics helpful in plant genomics to improve the crops have also been included in this volume. This volume has a chapter which describes the secrets of resistance development and further how these resistance are associated with human infectious diseases. This volume will be useful to the early career researcher in the development of research idea and develop their methodologies in the direction of bioinformatics and it will also give the insight to translate their findings. - Translational Bioinformatics - Health Informatics - Multi-omics



Omics


Omics
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Author : Debmalya Barh
language : en
Publisher: CRC Press
Release Date : 2013-03-26

Omics written by Debmalya Barh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-26 with Medical categories.


With the advent of new technologies and acquired knowledge, the number of fields in omics and their applications in diverse areas are rapidly increasing in the postgenomics era. Such emerging fields—including pharmacogenomics, toxicogenomics, regulomics, spliceomics, metagenomics, and environomics—present budding solutions to combat global challenges in biomedicine, agriculture, and the environment. OMICS: Applications in Biomedical, Agricultural, and Environmental Sciences provides valuable insights into the applications of modern omics technologies to real-world problems in the life sciences. Filling a gap in the literature, it offers a broad, multidisciplinary view of current and emerging applications of omics in a single volume. Written by highly experienced active researchers, each chapter describes a particular area of omics and the associated technologies and applications. Topics covered include: Proteomics, epigenomics, and pharmacogenomics Toxicogenomics and the assessment of environmental pollutants Applications of plant metabolomics Nutrigenomics and its therapeutic applications Microalgal omics and omics approaches in biofuel production Next-generation sequencing and omics technology for transgenic plant analysis Omics approaches in crop improvement Engineering dark-operative chlorophyll synthesis Computational regulomics Omics techniques for the analysis of RNA splicing New fields, including metagenomics, glycomics, and miRNA Breast cancer biomarkers for early detection Environomics strategies for environmental sustainability This timely book explores a wide range of omics application areas in the biomedical, agricultural, and environmental sciences. Throughout, it highlights working solutions as well as open problems and future challenges. Demonstrating the diversity of omics, it introduces readers to state-of-the-art developments and trends in omics-driven research.



Deep Learning And Parallel Computing Environment For Bioengineering Systems


Deep Learning And Parallel Computing Environment For Bioengineering Systems
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Author : Arun Kumar Sangaiah
language : en
Publisher: Academic Press
Release Date : 2019-07-26

Deep Learning And Parallel Computing Environment For Bioengineering Systems written by Arun Kumar Sangaiah and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-26 with Technology & Engineering categories.


Deep Learning and Parallel Computing Environment for Bioengineering Systems delivers a significant forum for the technical advancement of deep learning in parallel computing environment across bio-engineering diversified domains and its applications. Pursuing an interdisciplinary approach, it focuses on methods used to identify and acquire valid, potentially useful knowledge sources. Managing the gathered knowledge and applying it to multiple domains including health care, social networks, mining, recommendation systems, image processing, pattern recognition and predictions using deep learning paradigms is the major strength of this book. This book integrates the core ideas of deep learning and its applications in bio engineering application domains, to be accessible to all scholars and academicians. The proposed techniques and concepts in this book can be extended in future to accommodate changing business organizations' needs as well as practitioners' innovative ideas. - Presents novel, in-depth research contributions from a methodological/application perspective in understanding the fusion of deep machine learning paradigms and their capabilities in solving a diverse range of problems - Illustrates the state-of-the-art and recent developments in the new theories and applications of deep learning approaches applied to parallel computing environment in bioengineering systems - Provides concepts and technologies that are successfully used in the implementation of today's intelligent data-centric critical systems and multi-media Cloud-Big data



Deep Learning In Genetics And Genomics


Deep Learning In Genetics And Genomics
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Author : Khalid Raza
language : en
Publisher: Elsevier
Release Date : 2024-11-28

Deep Learning In Genetics And Genomics written by Khalid Raza and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-28 with Science categories.


Deep Learning in Genetics and Genomics vol. 1, Foundations and Applications, the intersection of deep learning and genetics opens up new avenues for advancing our understanding of the genetic code, gene regulation, and the broader genomics landscape. The book not only covers the most up-to-date advancements in the field of deep learning in genetics and genomics, but also a wide spectrum of (sub) topics including medical and clinical genetics, predictive medicine, transcriptomic, and gene expression studies. In 21 chapters Deep Learning in Genetics and Genomics vol. 1, Foundations and Applications describes how AI and DL have become increasingly useful in genetics and genomics research where both play a crucial role by accelerating research, improving the understanding of the human genome, and enabling personalized healthcare. From the fundamentals concepts and practical applications of deep learning algorithms to a wide range of challenging problems from genetics and genomics, Deep Learning in Genetics and Genomics vol. 1, Foundations and Applications creates a better knowledge of the biological and genetics mechanisms behind disease illnesses and improves the forecasting abilities using the different methodologies described. This title offers a unique resource for wider, deeper, and in-depth coverage of recent advancement in deep learning-based approaches in genetics and genomics, helping researchers process and interpret vast amounts of genetic data, identify patterns, and make discoveries that would be challenging or impossible using traditional methods. - Brings together fundamental concepts of genetics, genomics, and deep learning - Includes how to build background of solution methodologies and design of mathematical and logical algorithms - Delves into the intersection of deep learning and genetics, offering a comprehensive exploration of how deep learning techniques can be applied to various aspects of genomics



Deep Learning Techniques For Biomedical And Health Informatics


Deep Learning Techniques For Biomedical And Health Informatics
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Author : Sujata Dash
language : en
Publisher: Springer Nature
Release Date : 2019-11-14

Deep Learning Techniques For Biomedical And Health Informatics written by Sujata Dash and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-14 with Technology & Engineering categories.


This book presents a collection of state-of-the-art approaches for deep-learning-based biomedical and health-related applications. The aim of healthcare informatics is to ensure high-quality, efficient health care, and better treatment and quality of life by efficiently analyzing abundant biomedical and healthcare data, including patient data and electronic health records (EHRs), as well as lifestyle problems. In the past, it was common to have a domain expert to develop a model for biomedical or health care applications; however, recent advances in the representation of learning algorithms (deep learning techniques) make it possible to automatically recognize the patterns and represent the given data for the development of such model. This book allows new researchers and practitioners working in the field to quickly understand the best-performing methods. It also enables them to compare different approaches and carry forward their research in an important area that has a direct impact on improving the human life and health. It is intended for researchers, academics, industry professionals, and those at technical institutes and R&D organizations, as well as students working in the fields of machine learning, deep learning, biomedical engineering, health informatics, and related fields.



Computational Intelligence In Healthcare Informatics


Computational Intelligence In Healthcare Informatics
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Author : D. P. Acharjya
language : en
Publisher: Springer Nature
Release Date : 2024-02-21

Computational Intelligence In Healthcare Informatics written by D. P. Acharjya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-21 with Computers categories.


The book presents advancements in computational intelligence in perception with healthcare applications. Besides, the concepts, theory, and applications in various domains of healthcare systems including decision making in healthcare management, disease diagnosis, and electronic health records will be presented in a lucid manner. To achieve these objectives, both theoretical advances and its applications to healthcare problems will be stressed upon. This has been done to make the edited book more flexible and to stimulate further research interest in topics. The book is divided into four sections such as theoretical foundation of computational intelligence techniques, computational intelligence in analyzing health data, computational intelligence in electronic health record (EHR), and computational intelligence in ethical issues in health care.



Handbook Of Deep Learning Applications


Handbook Of Deep Learning Applications
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Author : Valentina Emilia Balas
language : en
Publisher: Springer
Release Date : 2019-02-25

Handbook Of Deep Learning Applications written by Valentina Emilia Balas and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-25 with Computers categories.


This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars.