Search

This book describes the state-of-the-art of chemoinformatics, bioinformatics, materials informatics and measurement/metrology informatics to develop drugs with desired activity or physicochemical properties and to optimize the functionality, efficacy, safety and quality of the compounds for drugs. Recently,'AI drug discovery', drug discovery research utilizing artificial intelligence technology such as machine learning, has attracted much attention. This book provides an overview of the four applied informatics fields and their applications in drug development for a wide spectrum of readers from learners to professional scientists in academia and industry. It focuses on the basic research stage of drug development with contributions from experts at the forefront of these fields. The authors hope that this book will be of assistance to explore new opportunities for collaboration between pharmaceutical science and informatics.

Blockchain is a new type of technology that combines and secures information exchange between different stakeholders such as medical practitioners, patients, healthcare providers, and other applicable parties. Among them, Blockchain Technology is one of the most important areas in the bioinformatics application of biomedical research and healthcare systems utilizing unique requirements and integration features. All the chapters are written by experts and researchers working in various areas of the biomedical and healthcare domain and they also dive into one of the most overlooked methodological, practical, and moral questions to secure and handle the enormous amount of data being generated from IoT-enabled biomedical and healthcare systems. In the beginning, this book presents an overview and then discusses open issues, challenges, and applicability aspect of Blockchain technology in healthcare. Then, this book presents a variety of perspectives on the most pressing questions in the field, for example: how IoT can connect billions of biomedical and healthcare information; how the blockchain-based secure access control mechanisms in biomedical and healthcare work; how to address the Quality-of-Service (QoS) and real-time accessibility requirements for healthcare applications; and how to ensure communication with efficiency. Also, it discusses Blockchain for IoT-enabled healthcare systems and presents a comparative analysis with respect to various performance evaluation metrics too.

This volume constitutes the proceedings of the 11th International Work-Conference on IWBBIO 2023, held in Meloneras, Gran Canaria, Spain, during July 15-17, 2022. The 54 full papers were carefully reviewed and selected from 148 submissions. They were organized in the following topical sections: Healthcare and Diseases, Machine Learning in Bioinformatics, New Advances in Deep Learning in Bioinformatics and Biomedicine, Novel Methodologies and Applications in Bioinformatics and Biomedicine.

This book is for individuals with a scientific background who aspire to apply machine learning within various natural science disciplines—such as physics, chemistry, biology, medicine, psychology and many more. It elucidates core mathematical concepts in an accessible and straightforward manner, maintaining rigorous mathematical integrity. For readers more versed in mathematics, the book includes advanced sections that are not prerequisites for the initial reading. It ensures concepts are clearly defined and theorems are proven where it's pertinent. Machine learning transcends the mere implementation and training of algorithms; it encompasses the broader challenges of constructing robust datasets, model validation, addressing imbalanced datasets, and fine-tuning hyperparameters. These topics are thoroughly examined within the text, along with the theoretical foundations underlying these methods. Rather than concentrating on particular algorithms this book focuses on the comprehensive concepts and theories essential for their application. It stands as an indispensable resource for any scientist keen on integrating machine learning effectively into their research. Numerous texts delve into the technical execution of machine learning algorithms, often overlooking the foundational concepts vital for fully grasping these methods. This leads to a gap in using these algorithms effectively across diverse disciplines. For instance, a firm grasp of calculus is imperative to comprehend the training processes of algorithms and neural networks, while linear algebra is essential for the application and efficient training of various algorithms, including neural networks. Absent a solid mathematical base, machine learning applications may be, at best, cursory, or at worst, fundamentally flawed. This book lays the foundation for a comprehensive understanding of machine learning algorithms and approaches.

This textbook introduces bioinformatics to students in mathematics with no biology background assumed and it provides solid mathematical tools for biology students along with an understanding of how to implement them in bioinformatics problems. In addition to the basics, the text offers new approaches to understanding biological sequences. The concise presentation distinguishes itself from others on the subject, discussing and providing principles that relate to current open problems in bioinformatics as well as considering a variety of models. The convex hull principle is highlighted, opening a new interdisciplinary research area at the intersection of biology, mathematics, and computer science. Prerequisites include first courses in linear algebra, probability and statistics, and mathematical analysis. Researchers in mathematics, biology, and math-biology, will also find aspects of this text useful. This textbook is written based on the authors'research works that have been published in various journals along with the lecture notes used when teaching bioinformatics courses at the University of Illinois at Chicago and at Tsinghua University. The content may be divided into two parts. The first part includes three chapters, introducing some basic concepts. Chapter 1 provides biological background in molecular biology for mathematicians. Chapter 2 describes biological databases that are commonly used. Chapter 3 is concerned with alignment methods including global/local alignment, heuristic alignment, and multiple alignment. The second part consisting of five chapters, describes several bioinformatics principles using a rigorous mathematical formulation. Chapter 4 introduces the time-frequency spectral principle and its applications in bioinformatics. In Chapters 5 and 6, two strategies are used, the graphical representation and the natural vector method, to represent biological sequences, and conduct sequence comparison and phylogenetic analysis without alignment. Chapter 7 presents the convex hull principle and shows how it can be used to mathematically determine whether a certain amino acid sequence can be a protein. The last chapter summarizes additional mathematical ideas relating to sequence comparisons, such as new feature vectors and metrics. This part focuses on the governing principle in biology and provides plenty of alignment-free methods, which cannot be found in any other book.

A Biologist's Guide to Artificial Intelligence: Building the Foundations of Artificial Intelligence and Machine Learning for Achieving Advancements in Life Sciences provides an overview of the basics of Artificial Intelligence for life science biologists. In 14 chapters/sections, readers will find an introduction to Artificial Intelligence from a biologist's perspective, including coverage of AI in precision medicine, disease detection, and drug development. The book also gives insights into the AI techniques used in biology and the applications of AI in food, and in environmental, evolutionary, agricultural, and bioinformatic sciences. Final chapters cover ethical issues surrounding AI and the impact of AI on the future. This book covers an interdisciplinary area and is therefore is an important subject matter resource and reference for researchers in biology and students pursuing their degrees in all areas of Life Sciences. It is also a useful title for the industry sector and computer scientists who would gain a better understanding of the needs and requirements of biological sciences and thus better tune the algorithms.Helps biologists succeed in understanding the concepts of Artificial Intelligence and machine learningEquips with new data mining strategies an easy interface into the world of Artificial IntelligenceEnables researchers to enhance their own sphere of researching Artificial Intelligence

This thoroughly updated edition reports on the current state of human computer interaction (HCI) in biomedicine and healthcare, focusing on the cognitive underpinnings of human interactions with people and technology. With health information technologies becoming increasingly vital tools for the practice of clinical medicine, this book draws from key theories, models and evaluation frameworks, and their application in biomedical contexts to apply this to current research in HCI. However, numerous challenges remain in order to fully realize their potential as instruments for advancing clinical care and enhancing patient safety. There is a general consensus that health IT has not realized its potential as a tool to facilitate clinical decision-making, the coordination of care and improvements in patient safety. Embracing sound principles of iterative design can yield significant dividends. It can also enhance practitioner's abilities to meet “meaningful use” requirements. The purpose of the book is two-fold: to address key gaps on the applicability of theories, models and evaluation frameworks of HCI and human factors for research in biomedical informatics. It highlights the state of the art, drawing from the current research in HCI. It also serves as a graduate level textbook highlighting key topics in HCI relevant for biomedical informatics, computer science and social science students working in the healthcare domain. Cognitive Informatics for Biomedicine: Human Computer Interaction in Healthcare is indispensable to those who want to ensure that the systems they build, and the interactive environments that they promote, will reflect the rigor and dedication to human-computer interaction principles that will ultimately enhance both the user's experience and the quality and safety of the care that is offered to patients. It is an essential reference to all who are interested in the application of these new techniques within healthcare, from students of informatics through to clinicians, informatics researchers and developers of health IT looking to incorporate them into their day-to-day workflow.

This book presents cutting-edge papers and perspectives on the transport of oxygen to tissues by scientists in a multitude of disciplines such as biochemistry, engineering, mathematics, medicine, physics, physiology, veterinary and complementary medicine. The book is composed of the following 7 parts: 50th Anniversary, Brain, Clinical applications, Methods and techniques, Tumor Oxygenation, Tissue oxygenation and Muscle. The articles in this book have been presented at the 50th annual meeting of the International Society on Oxygen Transport to Tissue (ISOTT 2023). Academics, clinical and industry researchers, engineers, as well as graduate students who are interested in oxygen transport to tissue will find this book a great reference and a useful learning resource.

This book constitutes the refereed proceedings of the 20th International Symposium on Bioinformatics Research and Applications, ISBRA 2024, held in Kunming, China, in July 19–21, 2024. The 93 full papers included in this book were carefully reviewed and selected from 236 submissions. The symposium provides a forum for the exchange of ideas and results among researchers, developers, and practitioners working on all aspects of bioinformatics and computational biology and their applications.

This book constitutes the refereed proceedings of the 20th International Symposium on Bioinformatics Research and Applications, ISBRA 2024, held in Kunming, China, in July 19–21, 2024. The 93 full papers included in this book were carefully reviewed and selected from 236 submissions. The symposium provides a forum for the exchange of ideas and results among researchers, developers, and practitioners working on all aspects of bioinformatics and computational biology and their applications.

This book introduces the rapidly evolving field of multi-omics in understanding the human microbiome. The book focuses on the technology used to generate multi-omics data, including advances in next-generation sequencing and other high-throughput methods. It also covers the application of artificial intelligence and machine learning algorithms to the analysis of multi-omics data, providing readers with an overview of the powerful computational tools that are driving innovation in this field. The chapter also explores the various bioinformatics databases and tools available for the analysis of multi-omics data. The book also delves into the application of multi-omics technology to the study of microbial diversity, including metagenomics, metatranscriptomics, and metaproteomics. The book also explores the use of these techniques to identify and characterize microbial communities in different environments, from the gut and oral microbiome to the skin microbiome and beyond. Towards theend, it focuses on the use of multi-omics in the study of microbial consortia, including mycology and the viral microbiome. The book also explores the potential of multi-omics to identify genes of biotechnological importance, providing readers with an understanding of the role that this technology could play in advancing biotech research. Finally, the book concludes with a discussion of the clinical applications of multi-omics technology, including its potential to identify disease biomarkers and develop personalized medicine approaches. Overall, this book provides readers with a comprehensive overview of this exciting field, highlighting the potential for multi-omics to transform our understanding of the microbial world.

This book is a concise but thorough introduction to the tools commonly used in pattern recognition and machine learning, including classification, dimensionality reduction, regression, and clustering, as well as recent popular topics such as deep neural networks and Gaussian process regression. The Second Edition is thoroughly revised, featuring a new chapter on the emerging topic of physics-informed machine learning and additional material on deep neural networks. Combining theory and practice, this book is suitable for the graduate or advanced undergraduate level classroom and self-study. It fills the need of a mathematically-rigorous text that is relevant to the practitioner as well, with datasets from applications in bioinformatics and materials informatics used throughout to illustrate the theory. These datasets are available from the book website to be used in end-of-chapter coding assignments based on python and Keras/Tensorflow. All plots in the text were generated using python scripts and jupyter notebooks, which can be downloaded from the book website.

This book constitutes the proceedings of the 21st International Conference on Comparative Genomics, RECOMB-CG 2024, which was held in Boston, MA, USA, during April 27–28, 2024. The 13 full papers presented in this book were carefully reviewed and selected from 21 submissions. The papers are divided into the following topical sections: phylogenetic networks; homology and phylogenetic reconstruction; tools for evolution reconstruction; genome rearrangements; and genome evolution.

This volume constitutes the proceedings of the 11th International Work-Conference on IWBBIO 2023, held in Gran Canaria, Spain, during July 15-17, 2022. The 54 full papers were carefully reviewed and selected from 148 submissions. They were organized in the following topical sections: Biomarker Identification, Biomedical Engineering, Biomedical Signal Analysis, E-Health.

In the evolving environment of bioinformatics, genomics, and computational biology, academic scholars are facing a challenging challenge – keeping informed about the latest research trends and findings. With unprecedented advancements in sequencing technologies, computational algorithms, and machine learning, these fields have become indispensable tools for drug discovery, disease research, genome sequencing, and more. As scholars strive to decode the language of DNA, predict protein structures, and navigate the complexities of biological data analysis, the need for a comprehensive and up-to-date resource becomes paramount. The Research Anthology on Bioinformatics, Genomics, and Computational Biology is a collection of a carefully curated selection of chapters that serves as the solution to the pressing challenge of keeping pace with the dynamic advancements in these critical disciplines. This anthology is designed to address the informational gap by providing scholars with a consolidated and authoritative source that sheds light on critical issues, innovative theories, and transformative developments in the field. It acts as a single reference point, offering insights into conceptual, methodological, technical, and managerial issues while also providing a glimpse into emerging trends and future opportunities. Within the anthology, scholars will find a wealth of knowledge spanning diverse topics, from gene selection using metaheuristics to the application of deep learning in biological big data analysis. It delves into cancer classification methodologies, cluster analysis with big data applications, and the impact of digitalization, robotics, and genomic research in livestock development. The book also explores precision drug screening for cystic fibrosis patients, presents a hybrid high-performance computing algorithm for gene regulatory network construction, and discusses the collaborative efforts between librarians and bioinformatics communities. The Research Anthology on Bioinformatics, Genomics, and Computational Biology offers the comprehensive solution needed to face the challenges presented to academic scholars. By providing a consolidated, authoritative, and up-to-date reference that empowers researchers, scientists, educators, and professionals to navigate and contribute to the forefront of transformative research in biological data analysis, this anthology provides a gateway to understanding and advancing the pivotal disciplines shaping the future of life sciences.

This updated 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 tensor decomposition. The author concludes by showing unsupervised methods and their application to a wide range of topics.

This book constitutes the refereed proceedings of the 20th International Symposium on Bioinformatics Research and Applications, ISBRA 2024, held in Kunming, China, in July 19–21, 2024. The 93 full papers included in this book were carefully reviewed and selected from 236 submissions. The symposium provides a forum for the exchange of ideas and results among researchers, developers, and practitioners working on all aspects of bioinformatics and computational biology and their applications.

Scan statistics, one of the most active research areas in applied probability and statistics, has seen a tremendous growth during the last 25 years. Google Scholar lists about 3,500 hits to references of articles on scan statistics since the year 2020, resulting in over 850 hits to articles per year. This is mainly due to extensive and diverse areas of science and technology where scan statistics have been employed, including: atmospheric and climate sciences, business, computer science, criminology, ecology, epidemiology, finance, genetics and genomics, geographic sciences, medical and health sciences, nutrition, pharmaceutical sciences, physics, quality control and reliability, social networks and veterinary science. This volume of the Handbook of Scan Statistics is a collection of forty chapters, authored by leading experts in the field, outlines the research and the breadthof applications of scan statistics to the numerous areas of science and technology listed above. These chapters present an overview of the theory, methods and computational techniques, related to research in the area of scan statistics and outline future developments. It contains extensive references to research articles, books and relevant computer software. Handbook of Scan Statistics is an excellent reference for researchers and graduate students in applied probability and statistics, as well as for scientists in research areas where scan statistics are used. This volume may also be used as a textbook for a graduate level course on scan statistics.

This book describes the bioinformatics research field, from its historical roots to the cutting-edge technologies. Many readers can discover the power of next-generation sequencing and genomic data analysis, uncover the secrets of single-cell genomics and transcriptomics, explore the metagenomics and microbiome analysis, and predict the protein structures using structural bioinformatics. Several case studies witnessing the fusion of bioinformatics and artificial intelligence, driving insights from vast biological datasets have also been explored. Other important aspects listed in the book are integrating the omics data for a holistic view of biological systems; experiencing the future of medicine with precision healthcare and personalized treatments; accelerating drug discovery and repurposing through computational approaches; agricultural genomics; and exploring the role of immunoinformatics in designing effective vaccines against infectious diseases.

The second volume of the book Emerging Human Viral Diseases discusses pathogenesis, diagnostics, and therapeutic strategies against viral encephalitis, gastroenteritis, and human immunodeficiency viral infections. The chapters discuss symptoms, diagnostics, and preventive strategies against viral infections. The book also reviews the epidemiology and evolution of viruses causing these infections. It also examines symptoms and strategies for developing novel diagnostics and the vaccine against these viruses. Toward the end, it discusses various biosafety principles for handling emerging viruses and reviews various bioinformatics tools and databases in virology research. This timely book offers valuable resource for the scientists working in the field of emerging viral infections and those involved in preventing, controlling, and managing viral diseases. Inclusively this book will be valuable guide covering most recent scientific progress in emerging human viral diseases and management and will serve as the best resource for undergraduates, graduates, medical professionals, researchers, public health physicians, and national and international health authorities.

This book informs on new trends, challenges, and solutions, in the multidisciplinary field of biomedical engineering. It covers traditional topics in biomechanics and biomedical signal processing, as well as recent trends relating to the applications of artificial intelligence and IoT in healthcare, wearable devices for patient monitoring, monitoring of medical devices, machine learning applications in medical data, among others. Gathering the second volume of the proceedings of the 9th European Medical and Biological Engineering Conference (EMBEC 2024), held on June 9-13, 2024, in Portorož, Slovenia, this book bridges fundamental and clinically-oriented research, emphasizing the role of translational research in biomedical engineering. It aims at inspiring and fostering communication and collaboration between engineers, physicists, biologists, physicians and other professionals dealing with cutting-edge themes in and advanced technologies serving the broad field of biology and healthcare.

This book provides an updated and in-depth introduction to the application of multiobjective optimization techniques in bioinformatics. In particular, it presents multiobjective solutions to a range of complex real-world bioinformatics problems. The authors first provide a comprehensive yet concise and self-contained introduction to relevant preliminary methodical constructions such as genetic algorithms, multiobjective optimization, data mining and several challenges in the bioinformatics domain. This is followed by several systematic applications of these techniques to real-world bioinformatics problems in the areas of gene expression and network biology. The book also features detailed theoretical and mathematical notes to facilitate reader comprehension. The book offers a valuable asset for a broad range of readers – from undergraduate to postgraduate, and as a textbook or reference work. Researchers and professionals can use the book not only to enrich their knowledge of multiobjective optimization and bioinformatics, but also as a comprehensive reference guide to applying and devising novel methods in bioinformatics and related domains.

This book presents a complete overview of COVID-19 and provides a series of in-depth analyses of the literature and a comprehensive discussion and perspectives on promising anti-SARS-CoV-2 agents based on the system of ethnopharmacology, which covers Chinese medicine, traditional medicines of India and Africa, Turkish folk medicine, essential oils, and some well-known medicinal plants. In this book, the current status of therapeutic strategies against COVID-19 was summarized and a perspective of potential options for the future was proposed. Based on ethnopharmacology, some well-established traditional herbal formulations and bioactive compounds with anti-virus activity were repurposed for managing COVID-19 and post-illness, including neurological disorders and kidney illness. Using drug discovery tools, promising immune enhancers were explored from phytochemicals against SARS-CoV-2. Nutraceuticals from dietary plants, spices, and fruits with anti-virus and antioxidant activities were recommended to prevent infection or severe illness caused by emerging variants. With the aid of systems pharmacology, researchers have gained insights into possible molecular mechanisms of anti-SARS-CoV-2 activity and have predicted a range of candidate compounds from medicinal plants to combat COVID-19. This book explores the current knowledge of drug discovery and ethnopharmacology for managing coronavirus diseases. The content proved the anti-SARS-CoV-2 activity from natural products and traditional herbal medicines. It contributes to the management of global public health and fits the goal of establishing “Good Health and Well-Being,” which is one of “The Sustainable Development Goals (SDGs) 2030'.

This volume constitutes the proceedings of the 10th International Work-Conference on IWBBIO 2023, held in Meloneras, Gran Canaria, Spain, during July 12-14, 2022. The total of 79 papers presented in the proceedings, was carefully reviewed and selected from 209 submissions. The papers cove the latest ideas and realizations in the foundations, theory, models, and applications for interdisciplinary and multidisciplinary research encompassing disciplines of computer science, mathematics, statistics, biology, bioinformatics, and biomedicine.

This volume constitutes the proceedings of the 10th International Work-Conference on IWBBIO 2023, held in Meloneras, Gran Canaria, Spain, during July 12-14, 2022. The total of 79 papers presented in the proceedings, was carefully reviewed and selected from 209 submissions. The papers cove the latest ideas and realizations in the foundations, theory, models, and applications for interdisciplinary and multidisciplinary research encompassing disciplines of computer science, mathematics, statistics, biology, bioinformatics, and biomedicine.

The second volume of the book-Protein-Protein Interactions (PPIs) provides an overview of various protein-protein interactions (PPIs) that are involved in various human diseases including cancer, neurodegenerative diseases, immune diseases, and inflammation. It summarizes the structure and ligand-based drug designing approaches for the discovery of small molecules that can inhibit PPIs in these diseases. The book discusses different computational and experimental tools that are used to determine the anomalous interactions underlying the diseases. Lastly, it also reviews the classical interactions between pathogens and hosts that are responsible for the pathophysiology of infectious diseases.

This textbook is an introductory guide to applied machine learning, specifically for biology students. It familiarizes biology students with the basics of modern computer science and mathematics and emphasizes the real-world applications of these subjects. The chapters give an overview of computer systems and programming languages to establish a basic understanding of the important concepts in computer systems. Readers are introduced to machine learning and artificial intelligence in the field of bioinformatics, connecting these applications to systems biology, biological data analysis and predictions, and healthcare diagnosis and treatment. This book offers a necessary foundation for more advanced computer-based technologies used in biology, employing case studies, real-world issues, and various examples to guide the reader from the basic prerequisites to machine learning and its applications.

This book presents methods and tools of network biology and bioinformatics for understanding the disease dynamics and identification of drug targets. The initial section of chapters introduce the theoretical aspects followed by the different applications for construction and analysis of biological networks, methods for identifying crucial nodes in networks, and network dynamics. The book covers the latest advances in the network medicine, exploring the different types of biological networks, and their applications. It further reviews the role of R language in the network-based approaches that help in understanding biological systems and identifying biological functions. Towards the end, the book explores the recent developments and applications in machine learning and its potential for advancing network biology. Finally, the book elucidates a comprehensive yet a representative description of challenges associated with the understanding of disease dynamics using network biology. Given its scope, the book is intended for researchers and advanced postgraduate students of bioinformatics, computational biology, and medical sciences. ​

This book updates knowledge on recent advances in computational, biophysical and bioinformatics tools/techniques and their practical applications in modern drug design and discovery paradigm. It also encompasses fundamental principles, advanced methodologies and applications of various CADD approaches including several cutting-edge areas; presenting recent developments covering ongoing trends in the field of computer-aided drug discovery. Having contributions by a global team of experts, the book is expected to be an ideal resource for drug discovery scientists, medicinal chemists, pharmacologists, toxicologists, phytochemists, biochemists, biologists, R&D personnel, researchers, students, teachers and those working in the field of drug discovery. It will fill the knowledge gaps that exist in the current CADD approaches and methodologies/ protocols being widely used in both academic and research practices. Further, a special focus on current status of various computational drug design approaches (SBDD, LBDD, de novo drug design, pharmacophore-based search), bioinformatics tools and databases, computational screening and modeling of phytochemicals/natural products, artificial intelligence and machine learning, and network pharmacology and systems biology would certainly guide researchers, students or readers to conduct their research in the emerging area(s) of interest. It is also expected to be highly beneficial to various stakeholders working in the pharmaceutical and biotechnology industries (R&D), the academic as well as research sectors.

This book broadly covers the given spectrum of disciplines in Computational Life Sciences, transforming it into a strong helping hand for teachers, students, practitioners and researchers. In Life Sciences, problem-solving and data analysis often depend on biological expertise combined with technical skills in order to generate, manage and efficiently analyse big data. These technical skills can easily be enhanced by good theoretical foundations, developed from well-chosen practical examples and inspiring new strategies. This is the innovative approach of Computational Life Sciences-Data Engineering and Data Mining for Life Sciences: We present basic concepts, advanced topics and emerging technologies, introduce algorithm design and programming principles, address data mining and knowledge discovery as well as applications arising from real projects. Chapters are largely independent and often flanked by illustrative examples and practical advise.

This updated and extended second edition of the textbook introduces the basic concepts of bioinformatics and enhances students'skills in the use of software and tools relevant to microbiology research. It discusses the most relevant methods for analysing data and teaches readers how to draw valid conclusions from the observations obtained. Free software and servers available on the Internet are presented in an updated version of 2023 and more advanced stand-alone software is proposed as a second option. In addition, new tools for microbial genome analysis and new flowcharts that complement the didactic elements have been added. Exercises and training questionnaires are included at the end of each chapter to facilitate learning. The book is aimed at Ph.D. students and advanced undergraduate students in microbiology, biotechnology, and (veterinary) medicine with little or basic knowledge of bioinformatics.

COVID-19 has brought us extensive research databases in the fields of biophysics, biology, and bioinformatics. To extract valuable structural bioinformatic information of SARS-CoV-2 structural and nonstructural proteins, it is necessary to work with large-scale datasets of molecular dynamics (MD) trajectories that need to be optimized. This monograph serves as a comprehensive guide to optimization-based MD studies of the molecular structures of SARS-CoV-2 proteins and RNA. The book begins by performing local optimization, taking into account the three-body movement and optimizing the noncovalent bonds of each molecular structure. The optimized structures reach a transition state that offers the best stability and lowest energy. The optimization process utilizes a hybrid strategy that combines mathematical optimization with various local search algorithms. This approach significantly reduces data volume while eliminating irrelevant bioinformatics data. To gain a thoroughunderstanding of molecular stability and the mechanism of action, it is essential to consider not only static NMR, X-ray, or cryo-EM structures but also dynamic information obtained through MD or Quantum Mechanics/Molecular Mechanics (QM/MM) simulations. These simulations capture the internal motions and dynamic processes of molecules. Furthermore, for each protein, the structural bioinformatics obtained from the optimized structure is validated by analyzing large-scale MD trajectory databases, which are openly and freely available online. The analysis includes key structural bioinformatics aspects such as salt bridge electrostatic interactions, hydrogen bonds, van der Waals interactions, and hydrophobic interactions specific to each SARS-CoV-2 molecular structure. The book also delves into discussions on drugs, vaccines, and the origins of the virus. Additionally, pandemic mathematical models, including those incorporating time delays, are explored. This book is particularly valuable for professionals working in practical computing roles within computational biochemistry, computational biophysics, optimization and molecular dynamics, structural bioinformatics, biological mathematics, and related fields. It serves as an accessible introduction to these disciplines and is also an excellent teaching resource for students.

This book constitutes the refereed proceedings of the 19th International Symposium on Bioinformatics Research and Applications, ISBRA 2023, held in Wrocław, Poland, during October 9–12, 2023.The 28 full papers and 16 short papers included in this book were carefully reviewed and selected from 89 submissions. They were organized in topical sections as follows: reconciling inconsistent molecular structures from biochemical databases; radiology report generation via visual recalibration and context gating-aware; sequence-based nanobody-antigen binding prediction; and hist2Vec: kernel-based embeddings for biological sequence classification.

This book helps readers discover the forefront of personalized medicine on clinical metabolomics and its applications in genetic diseases. This comprehensive guide offers a functional relationship map between cell components and genetic variations in various diseases, providing insights that can be applied to personalized medicine. The book covers the latest developments in metabolomics for health, with practical guidance for clinical experts looking to advance their laboratory techniques and career. The metabolomics profile is a powerful tool that has revolutionized our understanding of the relationship between genetics, clinical readouts, and disease outcomes. By integrating metabolomics with genomics and clinical phenotypes, the authors have developed diagnostic and prediction models that have vastly improved patient outcomes and deepened the understanding of disease mechanisms. This model has been successfully applied in various conditions, including inborn errors of metabolism, primary immunodeficiency, and endocrine disorders. However, integrating metabolomics with other omics datasets and clinical phenotypes requires careful study design, analytical tools, and data analysis and interpretation. This groundbreaking new book provides essential guidance for researchers, students, and professionals looking to leverage metabolomics in their own work, including biochemical and clinical geneticists, pharmacogenomics and pharmacometabolomics experts, pharmaceutics and diagnostic researchers, medical scientists, clinical dietitians, metabolic engineers, clinical chemists, and personalized medicine specialists.

This invaluable textbook presents a self-contained introduction to the field of bioinformatics. Providing a comprehensive breadth of coverage while remaining accessibly concise, the text promotes a deep understanding of the field, supported by basic mathematical concepts, an emphasis on biological knowledge, and a holistic approach that highlights the connections unifying bioinformatics with other areas of science.The thoroughly revised and enhanced fourth edition features new chapters focusing on regulation and control networks, the origins of life, evolution, statistics and causation, viruses, the microbiome, single cell analysis, drug discovery and forensic applications. This edition additionally includes new and updated material on the ontology of bioinformatics, data mining, ecosystems, and phenomics. Also covered are new developments in sequencing technologies, gene editing methods, and modelling of the brain, as well as state-of-the-art medical applications. Of specialtopicality is a new chapter on bioinformatics aspects of the coronavirus pandemic.Topics and features:Explains the fundamentals of set theory, combinatorics, probability, likelihood, causality, clustering, pattern recognition, randomness, complexity, systems, and networksDiscusses topics on ontogeny, phylogeny, genome structure, and regulation, as well as aspects of molecular biologyCritically examines the most significant practical applications, offering detailed descriptions of both the experimental process and the analysis of the dataProvides a varied selection of problems throughout the book, to stimulate further thinkingEncourages further reading through the inclusion of an extensive bibliographyThis classic textbook builds upon the successful formula of previous editions with coverage of the latest advances in this exciting and fast-moving field. With its interdisciplinary scope, this unique guide will prove to be an essential study companion to a broad audience of undergraduate and beginning graduate students, spanning computer scientists focusing on bioinformatics, students of the physical sciences seeking a helpful primer on biology, and biologists desiring to better understand the theory underlying important applications of information science in biology.Dr. Jeremy Ramsden is Hon. Prof. of Nanotechnology in the Department of Biomedical Research at the University of Buckingham, UK.

This book aims to promote the interaction among the scientific community to discuss applications of CS/AI with an interdisciplinary character, exploring the interactions between sub-areas of CS/AI, bioinformatics, chemoinformatics, and systems biology. The success of bioinformatics in recent years has been prompted by research in molecular biology and molecular medicine in several initiatives. This year's technical program presents both high quality and diversity, with contributions in well-established and evolving areas of research. The PACBB'23 technical program has selected 9 full papers in the main track and, as in past editions, it will be special issues in ranked journals. This symposium is organized by the LASI and Centro Algoritmi of the University of Minho (Portugal). The authors would like to thank all the contributing authors, the members of the program committee, national associations (AEPIA, APPIA), and the sponsors (AIR Institute).

This book facilitates both the theoretical background and applications of fuzzy, intuitionistic fuzzy and rough, fuzzy rough sets in the area of data science. This book provides various individual, soft computing, optimization and hybridization techniques of fuzzy and intuitionistic fuzzy sets with rough sets and their applications including data handling and that of type-2 fuzzy systems. Machine learning techniques are effectively implemented to solve a diversity of problems in pattern recognition, data mining and bioinformatics. To handle different nature of problems, including uncertainty, the book highlights the theory and recent developments on uncertainty, fuzzy systems, feature extraction, text categorization, multiscale modeling, soft computing, machine learning, deep learning, SMOTE, data handling, decision making, Diophantine fuzzy soft set, data envelopment analysis, centrally measures, social networks, Volterra–Fredholm integro-differential equation, Caputo fractional derivative, interval optimization, decision making, classification problems. This book is predominantly envisioned for researchers and students of data science, medical scientists and professional engineers.

In diesem Buch werden dem Leser einführend zentrale Ansätze der Bioinformatik entsprechend dem Fluss der genetischen Information von der Sequenzanalyse vom Virusgenom und seinen Proteinen über die Strukturvorhersage hin zu komplexeren Analysen (Interaktionen mit dem Wirt, Immunsystem) vorgestellt. Proteinnetzwerke, Metabolismus und Signalkaskaden erlauben dem Virus, eine hochgefährliche Infektion im Menschen zu erzeugen. Die Bioinformatik leistet wertvolle Hilfestellung bei der Diagnose, der Suche nach Behandlungsmöglichkeiten und vor allem bei der Herstellung von Impfstoffen und dem Vorhersehen des Pandemieverlaufs.Der InhaltBioinformatik ist einfach und schnell anzuwendenErste Detailanalysen (Sequenzen, Proteine, Gene)Analyse von Protein-NetzwerkenBioinformatik in der Infektionsbiologie und medizinische ImplikationenBioinformatik und Covid19 – ein globales PhänomenAnhang: Nützliche Webressourcen undLiteraturstellenDie ZielgruppenStudenten der Biologie und Medizin, die einen ersten Einblick in die Bioinformatik haben möchtenAllgemeines Publikum

This book brings together the latest updates from various subareas of biomedical engineering, providing readers with a broad overview of the current state of the art and the technological trends to be refined in the coming years with the goal of improving human health. It shows the important advances in each subfield, rehabilitation technology, computational systems applied to health, and medical devices, with practical examples. It includes topics not covered in other books in the area, such as digital health, bioprinting, organs-on-a-chip, the open data paradigm, and electrical impedance tomography. It is a short and easy-to-read book, and provides bibliographic references for the reader to go deeper into their areas of interest. This book is aimed at a very broad group of professionals and students in biomedical engineering and related areas, seeking to contextualize and understand the latest scientific advances in each subfield of biomedical engineering, including neuroengineering, regenerative medicine, additive manufacturing orthosis, postural analysis of Parkinson's patients, modelling and simulation using biomechanical open data, regenerative medicine, advanced drug delivery systems, bioprinting, biophotonic and electrical impedance tomography.

This book presents cutting-edge papers and perspectives on the transport of oxygen to tissues by scientists in a multitude of disciplines such as biochemistry, engineering, mathematics, medicine, physics, physiology, veterinary and complementary medicine. The book is composed of the following 6 parts: Brain Oxygenation and Function, Tumor Oxygenation and Metabolism, Muscle Oxygenation and Sports Medicine, Cell Metabolism and Tissue Oxygenation, Methodology of O2 Measurements, and Special Topics. The articles in this book have been presented at the 49th annual meeting of the International Society on Oxygen Transport to Tissue (ISOTT 2022). Academics, clinical and industry researchers, engineers, as well as graduate students who are interested in oxygen transport to tissue will find this book a great reference and a useful learning resource.

The book contains 35 chapters, in which you can find various examples of the development of methods and/or systems supporting medical diagnostics and therapy, related to biomedical imaging, signal and image processing, biomaterials and artificial organs, modelling of biomedical systems, which were presented as current research topics at the 23rd Polish Biocybernetics and Biomedical Engineering Conference, held at the Institute of Electronics, Lodz University of Technology in September 2023. The ongoing and dynamic development of AI-based data processing and analysis methods plays an increasingly important role in medicine. This book addresses these issues by presenting applications of such methods in various areas, such as disease diagnosis and prediction, particularly through the use of image data analysis algorithms. Other topics covered include personalized medicine, where multimodal patient data is acquired and analyzed, as well as robotic surgery and clinical decision support.The book is of interest to an advanced and broad readership, including researchers and engineers representing both medical, biological, and engineering viewpoints. Its readers may also be graduate and postgraduate students in various fields such as biomedical engineering, artificial intelligence, biomaterials, and medical electronics, as well as software developers in R&D departments working in the field of intelligent healthcare engineering.

This book constitutes the proceedings of the 16th Brazilian Symposium on Bioinformatics on Advances in Bioinformatics and Computational Biology, BSB 2023, which took place in Curitiba, Brazil, in June 2023. The 11 full papers and 3 short papers presented in this volume were carefully reviewed and selected from 24 submissions. The papers focus on bioinformatics, computational biology, Biological Databases, Biological Networks, Cheminformatics, Evolutionary Genomics, Computational Proteomics, Systems Biology, Drug Design, Genomics, Machine Learning applications in Bioinformatics, Metagenomics, Molecular Docking and Modeling, Molecular Evolution and Phylogenetics, Protein Structure and Modeling, Proteomics, Transcriptomics, Single-Cell Analysis, Workflows in Bioinformatics.

The 5th World Congress on Genetics, Geriatrics, and Neurodegenerative Diseases Research (GeNeDis 2022) focuses on the latest major challenges in scientific research, new drug targets, the development of novel biomarkers, new imaging techniques, novel protocols for early diagnosis of neurodegenerative diseases, and several other scientific advances, with the aim of better, safer, and healthier aging. This volume focuses on the sessions from the conference on Neuroscientific Advances.

Quantitative ultrasound (QUS) continues to mature as a research field and is primed to make a swift transition to routine preclinical and clinical applications. This book will serve two main purposes: Advanced education in QUS by providing a complete and thorough review of all theoretical, physical, and engineering aspects of QUS.Review of recent development of QUS by lead contributors in the research field. This 2nd edition will focus on 6 modern research topics related to quantitative ultrasound of soft tissues: Spectral-based methods for tissue characterization, tissue typing, cancer detection, etc.Attenuation estimation for tissue characterization and improving spectral based methodsEnvelope statistics analysis as a means of quantifying and imaging tissue properties.Ultrasound computed tomography for preclinical and clinical imaging.Scanning acoustic microscopy for formingimages of mechanical properties of soft tissues with micron resolution.Phantoms for quantitative ultrasound.

The 5th World Congress on Genetics, Geriatrics and Neurodegenerative Diseases Research (GeNeDis 2022) focuses on the latest major challenges in scientific research, new drug targets, the development of novel biomarkers, new imaging techniques, novel protocols for early diagnosis of neurodegenerative diseases, and several other scientific advances, with the aim of better, safer, and healthier aging. Computational methodologies for implementation on the discovery of biomarkers for neurodegenerative diseases are extensively discussed. This volume focuses on the sessions from the conference regarding computational biology and bioinformatics.

This book offers a gripping introduction to the fastest growing field of biology with easy-to-follow examples and a well-prepared appendix for the reader to cook up and experience everything right away.The book gets the reader started with the basics, such as how to easily find sequence information and then analyze it. In further chapters, the authors go into the various analysis options from RNA, DNA and proteins to entire metabolic pathways. Exciting examples from biology are chosen in each chapter to illustrate the analysis. Each chapter concludes with an exercise section that immediately puts what has been learned to use.The subject of this book is a must for any biology student, whether undergraduate or graduate, as bioinformatics is now unearthing amazing insights into the molecular basis of all living things. Computer science students and other students from related sciences will get a good introduction to bioinformatics, as biology and current topics (e.g. AI)are systematically introduced step by step alongside the software.Discover the key to life together with the authors and learn to understand the language of life. This book is a translation of the original German 2nd edition Bioinformatik by Thomas Dandekar and Meik Kunz, published by Springer-Verlag GmbH Germany, part of Springer Nature in 2021. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation. Springer Nature works continuously to further the development of tools for the production of books and on the related technologies to support the authors.

This book constitutes the proceedings of the 18th International Symposium on Bioinformatics Research and Applications, ISBRA 2022, held in Haifa, Israel, in November 14–17, 2022.The 30 full papers and 4 short papers presented in this book were carefully reviewed and selected from 72 submissions. They were organized in topical sections named: AI and disease; computational proteomics; biomedical imaging; drug screening and drug-drug interaction prediction; Biomedical data; sequencing data analysis.

This book presents cutting-edge research and developments in the field of biomedical engineering, with a special emphasis on results achieved in Vietnam and neighboring low- and middle-income countries. Covering both fundamental and applied research, and focusing on the theme of “Translational Healthcare Technology from Advanced to Low and Middle Income Countries in the Era of Covid and Digital Transformation”, it reports on the design, fabrication, and application of low-cost and portable medical devices, biosensors, and microfluidic devices, on improved methods for biological data acquisition and analysis, on nanoparticles for biological applications, and on new achievements in biomechanics, tissue engineering, and regeneration. It describes the developments of molecular and cellular biology techniques, neuroengineering techniques, and statistical and computational methods, including artificial intelligence, for biomedical applications. It also discusses strategies to addresssome relevant issues in biomedical education and entrepreneurship. Gathering the proceedings of the 9th International Conference on The Development of Biomedical Engineering in Vietnam, BME 9, held on December 27-29, 2022, in Ho Chi Minh, Vietnam, the book offers important answers to current challenges in the field and a source of inspiration for scientists, engineers, and researchers with various backgrounds working in different research institutes, companies, and countries.

This book is a revised version of the PhD dissertation written by the author to receive her PhD from the Department of Electronics, Information and Bioengineering at Politecnico di Milano, Italy. The work deals with one of the central objectives of the European Research Council project “Data-Driven Genomic Computing”, i.e., building an integrated repository for genomic data. It reflects the research adventure that starts from modeling biological data, goes through the challenges of integrating complex data and their describing metadata and finally builds tools for searching the data empowered by a semantic layer. The results of this thesis are part of a broad vision: the availability of conceptual models, related databases, and search systems for both humans and viruses genomics will provide important opportunities for research, especially if virus data will be connected to its host, the human being, who is the provider of genomic and phenotype information. In 2023, the PhD dissertation won the CAiSE PhD Award, granted to outstanding PhD theses in the field of information systems engineering.

What actually is a p-value for? And what is a significant result? This book answers such questions by providing a compact introduction to inferential statistics. Our major focus is on the logic of inferential statistics and hypothesis testing: We cover the logic behind statistical tests, we then walk through the most common procedures (t-test, analysis of variance with and without repeated measures, correlation/regression) and discuss pitfalls of data analysis. The book thus helps developing a solid understanding of how common test procedures work, and how to interpret their results correctly. Hands-on examples from everyday research – including exemplary calculations with the programs SPSS and R – supplement each chapter. In addition to classical methods, we briefly discuss recent developments in psychological research methods.This book is a translation of the original German 3rd edition of “Inferenzstatistik Verstehen” by Markus Janczyk and Roland Pfister. It is based on an AI-powered machine translation (by the service DeepL.com), with thorough follow-up editing by both authors.