Books in Bioinformatics and computational biology

1-10 of 93 results in All results

Multi-Omics Technology in Human Health and Diseases

• 1st Edition
• March 1, 2025
• Muzafar A Macha + 2 more
• English
• Paperback 978-0-443-13595-8

  9 7 8 - 0 - 4 4 3 - 1 3 5 9 5 - 8
• eBook 978-0-443-13596-5

  9 7 8 - 0 - 4 4 3 - 1 3 5 9 6 - 5

Multi-Omics Technology in Human Health and Diseases: Genomics, Epigenomics, Transcriptomics, Proteomics, Metabolomics, Radiomics, Multi-omic offers an advanced exploration into the comprehensive understanding of disease etiology and prognosis through multiomics approaches. This authoritative volume delves into the applications of multiomics technology in elucidating complex human health conditions and diseases. It introduces the technology's potential for biomarker identification, drug discovery, and disease prognostication. For a thorough understanding of human health and diseases, particularly cancer, it is essential to integrate knowledge of molecular biomarkers across multiple omics levels, including the genome, epigenome, transcriptome, proteome, and metabolome. This resource addresses the current gaps in knowledge among students and researchers, providing in-depth coverage of multiomics technology and its implementation in scientific research and discovery.Multi-Omics Technology in Human Health and Diseases: Genomics, Epigenomics, Transcriptomics, Proteomics, Metabolomics, Radiomics, Multi-omic is a pioneering resource that presents cutting-edge information on contemporary multiomics technologies for big data interpretation and their applications in deciphering complex human pathobiology. This comprehensive guide is indispensable for researchers, academics, students, and industry professionals alike.

Deep Learning in Genetics and Genomics

• 1st Edition
• November 28, 2024
• Khalid Raza
• English
• Paperback 978-0-443-27523-4

  9 7 8 - 0 - 4 4 3 - 2 7 5 2 3 - 4

Deep Learning in Genetics and Genomics: Vol. 2 (Advanced Applications) delves into the Deep Learning methods and their applications in various fields of studies, including genetics and genomics, bioinformatics, health informatics and medical informatics generating the momentum of today's developments in the field. In 25 chapters this title covers advanced applications in the field which includes deep learning in predictive medicines), analysis of genetic and clinical features, transcriptomics and gene expression patterns analysis, clinical decision support in genetic diagnostics, deep learning in personalised genomics and gene editing, and understanding genetic discoveries through Explainable AI. Further, it also covers various deep learning-based case studies, making this book a unique resource for wider, deeper, and in-depth coverage of recent advancement in deep learning based approaches. This volume is not only a valuable resource for health educators, clinicians, and healthcare professionals but also to graduate students of genetics, genomics, biology, biostatistics, biomedical sciences, bioinformatics, and interdisciplinary sciences.

Deep Learning in Genetics and Genomics

• 1st Edition
• November 28, 2024
• Khalid Raza
• English
• Paperback 978-0-443-27574-6

  9 7 8 - 0 - 4 4 3 - 2 7 5 7 4 - 6

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.

The Three Functional States of Proteins

• 1st Edition
• November 17, 2024
• Timir Tripathi + 1 more
• English
• Paperback 978-0-443-21809-5

  9 7 8 - 0 - 4 4 3 - 2 1 8 0 9 - 5
• eBook 978-0-443-21810-1

  9 7 8 - 0 - 4 4 3 - 2 1 8 1 0 - 1

The Three Functional States of Proteins explores how structured proteins, intrinsically disordered proteins, and phase separated proteins contribute to the complexity of cellular life, and offers insights into their roles in both health and disease. It discusses the latest research findings and highlight groundbreaking discoveries and innovative methodologies used to study these protein states.Traditionally, the different states of proteins have been defined based on their structures and functions. However, it is becoming increasingly clear that these criteria alone may not be sufficient to capture the complex and multifaceted properties of these molecules. Definitions based on thermodynamics and kinetics are now recognized as potentially more appropriate for comprehensively understanding protein states. Emerging evidence indicates that under physiological conditions, a majority of proteins possess the capability to exist in and transition between the native, droplet, and amyloid states. These distinct states play crucial roles in various cellular functions, influenced significantly by their physicochemical and structural properties. The book also considers the interactions among these states and discusses how their internal organization as individual molecules, as well as their collective organization as molecular assemblies are stabilized. Furthermore, it examines the processes by which these states are formed and the cellular functions associated with each specific state.

Mining Biomedical Text, Images and Visual Features for Information Retrieval

• 1st Edition
• November 15, 2024
• Sujata Dash + 3 more
• English
• Paperback 978-0-443-15452-2

  9 7 8 - 0 - 4 4 3 - 1 5 4 5 2 - 2
• eBook 978-0-443-15451-5

  9 7 8 - 0 - 4 4 3 - 1 5 4 5 1 - 5

Mining Biomedical Text, Images and Visual Features for Information Retrieval provides broad coverage of the concepts, themes, and instrumentalities of the important, evolving area of biomedical text, images, and visual features towards information retrieval. The book aims to encourage an even wider adoption of IR methods for assisting in problem-solving and to stimulate research that may lead to additional innovations in this area of research. Topics covered include Internet of Things for health informatics; data privacy; smart healthcare; medical image processing; 3D medical images; evolutionary computing; deep learning; medical ontology; linguistic indexing; lexical analysis; and domain specific semantic categories in biomedical applications. This is a valuable resource for researchers and graduate students who are interested to learn more about data mining techniques to improve their research work.

Next Generation eHealth

• 1st Edition
• September 30, 2024
• Miltiadis Lytras + 3 more
• English
• Paperback 978-0-443-13619-1

  9 7 8 - 0 - 4 4 3 - 1 3 6 1 9 - 1
• eBook 978-0-443-13620-7

  9 7 8 - 0 - 4 4 3 - 1 3 6 2 0 - 7

Next Generation eHealth: Applied Data Science, Machine Learning and Extreme Computational Intelligence discusses the emergence, the impact, and the potential of sophisticated computational capabilities in healthcare. This book provides useful therapeutic targets to improve diagnosis, therapies, and prognosis of diseases, as well as helping with the establishment of better and more efficient next-generation medicine and medical systems. Machine learning as a field greatly contributes to next-generation medical research with the goal of improving medicine practices and medical Systems. As a contributing factor to better health outcomes, this book highlights the need for advanced training of professionals from various health areas, clinicians, educators, and social professionals who deal with patients. Content illustrates current issues and future promises as they pertain to all stakeholders, including informaticians, professionals in diagnostics, key industry experts in biotech, pharma, administrators, clinicians, patients, educators, students, health professionals, social scientists and legislators, health providers, advocacy groups, and more. With a focus on machine learning, deep learning, and neural networks, this volume communicates in an integrated, fresh, and novel way the impact of data science and computational intelligence to diverse audiences.

Artificial Intelligence in Biomedical and Modern Healthcare Informatics

• 1st Edition
• September 27, 2024
• M. A. Ansari + 4 more
• English
• Paperback 978-0-443-21870-5

  9 7 8 - 0 - 4 4 3 - 2 1 8 7 0 - 5
• eBook 978-0-443-21871-2

  9 7 8 - 0 - 4 4 3 - 2 1 8 7 1 - 2

Artificial Intelligence in Biomedical and Modern Healthcare Informatics provides a deeper understanding of the current trends in AI and machine learning within healthcare diagnosis, its practical approach in healthcare, and gives insight into different wearable sensors and its device module to help doctors and their patients in enhanced healthcare system.The primary goal of this book is to detect difficulties and their solutions to medical practitioners for the early detection and prediction of any disease.The 56 chapters in the volume provide beginners and experts in the medical science field with general pictures and detailed descriptions of imaging and signal processing principles and clinical applications.With forefront applications and up-to-date analytical methods, this book captures the interests of colleagues in the medical imaging research field and is a valuable resource for healthcare professionals who wish to understand the principles and applications of signal and image processing and its related technologies in healthcare.

The Physics of Protein Structure and Dynamics

• 1st Edition
• September 23, 2024
• Reinhard Schweitzer-Stenner
• English
• eBook 978-0-443-15965-7

  9 7 8 - 0 - 4 4 3 - 1 5 9 6 5 - 7

The Physics of Protein Structure and Dynamics looks at various aspects of protein structure and dynamics from a physico-chemical point of view. It goes into some depth regarding the description of non-covalent forces that determine the relative stability of folded and unfolded proteins. Anharmonic protein dynamics involving motions between different minima of a rugged Gibbs energy landscape is described in great detail. The book combines various aspects of the protein folding/unfolding processes with an overview of intrinsically disordered proteins, which have attracted considerable interest of the protein community over the last 25 years but are thus far underrepresented in classroom-oriented textbooks. The book looks at protein folding and intrinsically disordered proteins as heavily interrelated topics that need to be viewed together. Furthermore, it presents some basic physico-chemical aspects of protein/peptide self-assembly into nanoscale fibrils. Intrinsically disordered peptides and proteins play a major role particularly in aggregation and self-assembly processes that lead to various diseases (Alzheimer, Parkinson, Huntington, Mad-Cow). Therefore, the relevance of protein disorder for protein self-assembly deserves a closer look. Protein self-assembly cannot be separated from protein folding since it is frequently the product of misfolding. With regard to modern theories, the folding processes are linked to insights on protein dynamics and the discovered relationship between proteins and spin glasses.

Planning, Writing and Reviewing Medical Device Clinical and Performance Evaluation Reports (CERs/PERs)

• 1st Edition
• September 19, 2024
• Joy Frestedt
• English
• Paperback 978-0-443-22063-0

  9 7 8 - 0 - 4 4 3 - 2 2 0 6 3 - 0
• eBook 978-0-443-22064-7

  9 7 8 - 0 - 4 4 3 - 2 2 0 6 4 - 7

A Practical Guide to Planning, Writing, and Reviewing Medical Device Clinical Evaluation Reports guides readers through clinical data evaluation of medical devices that is in compliance with the EU MDR requirements and other similar regulatory requirements throughout the world. This book brings together knowledge learned as the author constructed hundreds of CERs and taught thousands of learners on how to conduct clinical data evaluations. This book will support training for clinical engineers, clinical evaluation scientists, and experts reviewing medical device CERs, and will help individual writers, teams and companies to develop stronger, more robust CERs.

Applied Multivariate Statistical Analysis in Medicine

• 1st Edition
• August 21, 2024
• Jingmei Jiang
• English
• Paperback 978-0-443-23587-0

  9 7 8 - 0 - 4 4 3 - 2 3 5 8 7 - 0
• eBook 978-0-443-23588-7

  9 7 8 - 0 - 4 4 3 - 2 3 5 8 8 - 7

Applied Multivariate Statistical Analysis in Medicine provides a multivariate conceptual framework that allows readers to understand the interconnectivity and interrelations among variables, which maintains the intrinsic precision of statistical theories. With a strong focus on the fundamental concepts of multivariate statistical analysis, the book also gives insight into the applications of multivariate distribution in biomedical fields. In 14 chapters, Applied Multivariate Statistical Analysis in Medicine covers the main topics of multivariate analysis methods widely used in health science research. The content is organized progressively from fundamental concepts to sophisticated methods. It begins with basic descriptive statistics in multivariate analysis and follows with parameter estimation, in addition to the hypothesis testing of a multivariate normal distribution, which has heavy applications in biomedical fields where the relationships among approximately normal variables are of great interest. Keeping mathematics to a minimum, considerable emphasis is placed on explanations and real-world applications of core principles to maintain a good balance between introducing theory and cultivating problem-solving skills. This book is a very valuable reference text for clinicians, medical researchers, and other researchers across medical and biomedical disciplines, all of whom confront increasingly complex statistical methods during the analysis and presentation of their results.