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| computer in biology and medicine: Regenerative Biology and Medicine David L. Stocum, 2012-06-07 Regenerative Biology and Medicine, Second Edition — Winner of a 2013 Highly Commended BMA Medical Book Award for Medicine — discusses the fundamentals of regenerative biology and medicine. It provides a comprehensive overview, which integrates old and new data into an ever-clearer global picture. The book is organized into three parts. Part I discusses the mechanisms and the basic biology of regeneration, while Part II deals with the strategies of regenerative medicine developed for restoring tissue, organ, and appendage structures. Part III reflects on the achievements of regenerative biology and medicine; future challenges; bioethical issues that need to be addressed; and the most promising developments in regenerative medicine. The book is designed for multiple audiences: undergraduate students, graduate students, medical students and postdoctoral fellows, and research investigators interested in an overall synthesis of this field. It will also appeal to investigators from fields not directly related to regenerative biology and medicine, such as chemistry, informatics, computer science, mathematics, physics, and engineering. - Highly Commended 2013 BMA Medical Book Award for Medicine - Includes coverage of skin, hair, teeth, cornea, and central neural tissues - Provides description of regenetive medicine in digestive, respiratory, urogenital, musculoskeletal, and cardiovascular systems - Includes amphibians as powerful research models with discussion of appendage regeneration in amphibians and mammals |
| computer in biology and medicine: Artificial Intelligence in Medicine David Riaño, Szymon Wilk, Annette ten Teije, 2019-06-19 This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning. |
| computer in biology and medicine: Analyzing Network Data in Biology and Medicine Nataša Pržulj, 2019-03-28 Introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning, using real-world biological and medical examples. |
| computer in biology and medicine: Biomedical Informatics Edward H. Shortliffe, James J. Cimino, 2013-12-02 The practice of modern medicine and biomedical research requires sophisticated information technologies with which to manage patient information, plan diagnostic procedures, interpret laboratory results, and carry out investigations. Biomedical Informatics provides both a conceptual framework and a practical inspiration for this swiftly emerging scientific discipline at the intersection of computer science, decision science, information science, cognitive science, and biomedicine. Now revised and in its third edition, this text meets the growing demand by practitioners, researchers, and students for a comprehensive introduction to key topics in the field. Authored by leaders in medical informatics and extensively tested in their courses, the chapters in this volume constitute an effective textbook for students of medical informatics and its areas of application. The book is also a useful reference work for individual readers needing to understand the role that computers can play in the provision of clinical services and the pursuit of biological questions. The volume is organized so as first to explain basic concepts and then to illustrate them with specific systems and technologies. |
| computer in biology and medicine: Advanced Imaging in Biology and Medicine Ch.W. Sensen, Benedikt Hallgrimsson, 2008-12-03 A picture says more than a thousand words. This is something that we all know to be true. Imaging has been important since the early days of medicine and bi- ogy, as seen in the anatomical studies of Leonardo Da Vinci or Andreas Vesalius. More than 100 years ago, the ?rst noninvasive imaging technologies, such as K- rad Roentgen’s X-ray technology,were applied to the medical ?eld—and while still crude—revolutionized medical diagnosis. Today, every patient will be exposed to some kind of advanced imaging technology such as medical resonance imaging, computed tomography or four-dimensional ultrasound during their lifetime. Many diseases, such as brain tumors, are initially diagnosed solely by imaging, and most of the surgical planning relies on the patient imagery. 4D ultrasound is available to expecting parents who wish to create unique early memories of the new baby, and it may soon be used for the morphometric diagnosis of malformations that may one day be treatable—inutero! Light and electron microscopy are unequal brethren, which have contributed to most of our knowledge about the existence and organization of cells, tissues and microorganisms. Every student of biology or medicine is introduced to the fascinating images of the microcosm. New advances have converted these im- ing technologies, which were considered by many to be antiquated, into powerful tools for research in systems biology and related ?elds. |
| computer in biology and medicine: Biomedical Informatics Edward H. Shortliffe, James J. Cimino, 2006-12-02 This book focuses on the role of computers in the provision of medical services. It provides both a conceptual framework and a practical approach for the implementation and management of IT used to improve the delivery of health care. Inspired by a Stanford University training program, it fills the need for a high quality text in computers and medicine. It meets the growing demand by practitioners, researchers, and students for a comprehensive introduction to key topics in the field. Completely revised and expanded, this work includes several new chapters filled with brand new material. |
| computer in biology and medicine: Modeling in Computational Biology and Biomedicine Frédéric Cazals, Pierre Kornprobst, 2012-11-06 Computational biology, mathematical biology, biology and biomedicine are currently undergoing spectacular progresses due to a synergy between technological advances and inputs from physics, chemistry, mathematics, statistics and computer science. The goal of this book is to evidence this synergy by describing selected developments in the following fields: bioinformatics, biomedicine and neuroscience. This work is unique in two respects - first, by the variety and scales of systems studied and second, by its presentation: Each chapter provides the biological or medical context, follows up with mathematical or algorithmic developments triggered by a specific problem and concludes with one or two success stories, namely new insights gained thanks to these methodological developments. It also highlights some unsolved and outstanding theoretical questions, with a potentially high impact on these disciplines. Two communities will be particularly interested in this book. The first one is the vast community of applied mathematicians and computer scientists, whose interests should be captured by the added value generated by the application of advanced concepts and algorithms to challenging biological or medical problems. The second is the equally vast community of biologists. Whether scientists or engineers, they will find in this book a clear and self-contained account of concepts and techniques from mathematics and computer science, together with success stories on their favorite systems. The variety of systems described represents a panoply of complementary conceptual tools. On a practical level, the resources listed at the end of each chapter (databases, software) offer invaluable support for getting started on a specific topic in the fields of biomedicine, bioinformatics and neuroscience. |
| computer in biology and medicine: Intelligence-Based Medicine Anthony C. Chang, 2020-06-27 Intelligence-Based Medicine: Data Science, Artificial Intelligence, and Human Cognition in Clinical Medicine and Healthcare provides a multidisciplinary and comprehensive survey of artificial intelligence concepts and methodologies with real life applications in healthcare and medicine. Authored by a senior physician-data scientist, the book presents an intellectual and academic interface between the medical and the data science domains that is symmetric and balanced. The content consists of basic concepts of artificial intelligence and its real-life applications in a myriad of medical areas as well as medical and surgical subspecialties. It brings section summaries to emphasize key concepts delineated in each section; mini-topics authored by world-renowned experts in the respective key areas for their personal perspective; and a compendium of practical resources, such as glossary, references, best articles, and top companies. The goal of the book is to inspire clinicians to embrace the artificial intelligence methodologies as well as to educate data scientists about the medical ecosystem, in order to create a transformational paradigm for healthcare and medicine by using this emerging new technology. - Covers a wide range of relevant topics from cloud computing, intelligent agents, to deep reinforcement learning and internet of everything - Presents the concepts of artificial intelligence and its applications in an easy-to-understand format accessible to clinicians and data scientists - Discusses how artificial intelligence can be utilized in a myriad of subspecialties and imagined of the future - Delineates the necessary elements for successful implementation of artificial intelligence in medicine and healthcare |
| computer in biology and medicine: Computer Simulation and Data Analysis in Molecular Biology and Biophysics Victor Bloomfield, 2009-06-05 This book provides an introduction to two important aspects of modern bioch- istry, molecular biology, and biophysics: computer simulation and data analysis. My aim is to introduce the tools that will enable students to learn and use some f- damental methods to construct quantitative models of biological mechanisms, both deterministicandwithsomeelementsofrandomness;tolearnhowconceptsofpr- ability can help to understand important features of DNA sequences; and to apply a useful set of statistical methods to analysis of experimental data. The availability of very capable but inexpensive personal computers and software makes it possible to do such work at a much higher level, but in a much easier way, than ever before. TheExecutiveSummaryofthein?uential2003reportfromtheNationalAcademy of Sciences, “BIO 2010: Transforming Undergraduate Education for Future - search Biologists” [12], begins The interplay of the recombinant DNA, instrumentation, and digital revolutions has p- foundly transformed biological research. The con?uence of these three innovations has led to important discoveries, such as the mapping of the human genome. How biologists design, perform, and analyze experiments is changing swiftly. Biological concepts and models are becoming more quantitative, and biological research has become critically dependent on concepts and methods drawn from other scienti?c disciplines. The connections between the biological sciences and the physical sciences, mathematics, and computer science are rapidly becoming deeper and more extensive. |
| computer in biology and medicine: Perl Programming for Medicine and Biology Jules J. Berman, 2007 Written for biomedical professionals and hospital practitioners interested in creating their own programs, Perl Programming for Medicine and Biology, discusses and reviews biomedical data resources, data standards, data organization, medicolegal and ethical conduct for data miners, and grants-related data sharing responsibilities. It teaches readers the basic Perl programming skills necessary for collecting, analyzing, and distributing biomedical data and provides solutions to in-depth problems that face researchers and healthcare professionals. Non-technical Background sections open each chapter to help non-programmers easily comprehend programming procedures. Explanations are provided for the biomedical issues underlying the Perl scripts that follow, and examples of real-world implementation are provided. Perl Programming for Medicine and Biology will show you how to transform, merge, and examine large and complex databases with ease. |
| computer in biology and medicine: Health Informatics: Practical Guide for Healthcare and Information Technology Professionals (Sixth Edition) Robert E. Hoyt, Ann K. Yoshihashi, 2014 Health Informatics (HI) focuses on the application of Information Technology (IT) to the field of medicine to improve individual and population healthcare delivery, education and research. This extensively updated fifth edition reflects the current knowledge in Health Informatics and provides learning objectives, key points, case studies and references. |
| computer in biology and medicine: The Computer-Based Patient Record Committee on Improving the Patient Record, Institute of Medicine, 1997-10-28 Most industries have plunged into data automation, but health care organizations have lagged in moving patients' medical records from paper to computers. In its first edition, this book presented a blueprint for introducing the computer-based patient record (CPR). The revised edition adds new information to the original book. One section describes recent developments, including the creation of a computer-based patient record institute. An international chapter highlights what is new in this still-emerging technology. An expert committee explores the potential of machine-readable CPRs to improve diagnostic and care decisions, provide a database for policymaking, and much more, addressing these key questions: Who uses patient records? What technology is available and what further research is necessary to meet users' needs? What should government, medical organizations, and others do to make the transition to CPRs? The volume also explores such issues as privacy and confidentiality, costs, the need for training, legal barriers to CPRs, and other key topics. |
| computer in biology and medicine: Guide for the Care and Use of Laboratory Animals National Research Council, Division on Earth and Life Studies, Institute for Laboratory Animal Research, Committee for the Update of the Guide for the Care and Use of Laboratory Animals, 2011-01-27 A respected resource for decades, the Guide for the Care and Use of Laboratory Animals has been updated by a committee of experts, taking into consideration input from the scientific and laboratory animal communities and the public at large. The Guide incorporates new scientific information on common laboratory animals, including aquatic species, and includes extensive references. It is organized around major components of animal use: Key concepts of animal care and use. The Guide sets the framework for the humane care and use of laboratory animals. Animal care and use program. The Guide discusses the concept of a broad Program of Animal Care and Use, including roles and responsibilities of the Institutional Official, Attending Veterinarian and the Institutional Animal Care and Use Committee. Animal environment, husbandry, and management. A chapter on this topic is now divided into sections on terrestrial and aquatic animals and provides recommendations for housing and environment, husbandry, behavioral and population management, and more. Veterinary care. The Guide discusses veterinary care and the responsibilities of the Attending Veterinarian. It includes recommendations on animal procurement and transportation, preventive medicine (including animal biosecurity), and clinical care and management. The Guide addresses distress and pain recognition and relief, and issues surrounding euthanasia. Physical plant. The Guide identifies design issues, providing construction guidelines for functional areas; considerations such as drainage, vibration and noise control, and environmental monitoring; and specialized facilities for animal housing and research needs. The Guide for the Care and Use of Laboratory Animals provides a framework for the judgments required in the management of animal facilities. This updated and expanded resource of proven value will be important to scientists and researchers, veterinarians, animal care personnel, facilities managers, institutional administrators, policy makers involved in research issues, and animal welfare advocates. |
| computer in biology and medicine: Use of Computers in Biology and Medicine Robert Steven Ledley, 1965 |
| computer in biology and medicine: Medical Image Analysis Alejandro Frangi, Jerry Prince, Milan Sonka, 2023-09-20 Medical Image Analysis presents practical knowledge on medical image computing and analysis as written by top educators and experts. This text is a modern, practical, self-contained reference that conveys a mix of fundamental methodological concepts within different medical domains. Sections cover core representations and properties of digital images and image enhancement techniques, advanced image computing methods (including segmentation, registration, motion and shape analysis), machine learning, how medical image computing (MIC) is used in clinical and medical research, and how to identify alternative strategies and employ software tools to solve typical problems in MIC. - An authoritative presentation of key concepts and methods from experts in the field - Sections clearly explaining key methodological principles within relevant medical applications - Self-contained chapters enable the text to be used on courses with differing structures - A representative selection of modern topics and techniques in medical image computing - Focus on medical image computing as an enabling technology to tackle unmet clinical needs - Presentation of traditional and machine learning approaches to medical image computing |
| computer in biology and medicine: Physics in Biology and Medicine Paul Davidovits, 2008 This third edition covers topics in physics as they apply to the life sciences, specifically medicine, physiology, nursing and other applied health fields. It includes many figures, examples and illustrative problems and appendices which provide convenient access to the most important concepts of mechanics, electricity, and optics. |
| computer in biology and medicine: Fractals in Biology and Medicine Gabriele A. Losa, Theo F. Nonnenmacher, Ewald R. Weibel, 1994 In March 2000 leading scientists gathered at the Centro Seminariale Monte Verità, Ascona, Switzerland, for the Third International Symposium on Fractals 2000 in Biology and Medicine. This interdisciplinary conference provided stimulating contributions from the very topical field Fractals in Biology and Medicine. This volume highlights the growing power and efficacy of the fractal geometry in understanding how to analyze living phenomena and complex shapes. |
| computer in biology and medicine: Systematic James R. Valcourt, 2017-02-07 A brilliant young scientist introduces us to the fascinating field that is changing our understanding of how the body works and the way we can approach healing. SYSTEMATIC is the first book to introduce general readers to systems biology, which is improving medical treatments and our understanding of living things. In traditional bottom-up biology, a biologist might spend years studying how a single protein works, but systems biology studies how networks of those proteins work together--how they promote health and how to remedy the situation when the system isn't functioning properly. Breakthroughs in systems biology became possible only when powerful computer technology enabled researchers to process massive amounts of data to study complete systems, and has led to progress in the study of gene regulation and inheritance, cancer drugs personalized to an individual's genetically unique tumor, insights into how the brain works, and the discovery that the bacteria and other microbes that live in the gut may drive malnutrition and obesity. Systems biology is allowing us to understand more complex phenomena than ever before. In accessible prose, SYSTEMATIC sheds light not only on how systems within the body work, but also on how research is yielding new kinds of remedies that enhance and harness the body's own defenses. |
| computer in biology and medicine: Computational Biology Scott T. Kelley, Dennis Didulo, 2018-01-01 This textbook is for anyone who needs to learn the basics of bioinformatics—the use of computational methods to better understand biological systems. Computational Biology covers the principles and applications of the computational methods used to study DNA, RNA, and proteins, including using biological databases such as NCBI and UniProt; performing BLAST, sequence alignments, and structural predictions; and creating phylogenetic trees. It includes a primer that can be used as a jumping off point for learning computer programming for bioinformatics. This text can be used as a self-study guide, as a course focused on computational methods in biology/bioinformatics, or to supplement general courses that touch on topics included within the book. Computational Biology's robust interactive online components “gamify” the study of bioinformatics, allowing the reader to practice randomly generated problems on their own time to build confidence and skill and gain practical real-world experience. The online component also assures that the content being taught is up to date and accurately reflects the ever-changing landscape of bioinformatics web-based programs. |
| computer in biology and medicine: Beyond the Molecular Frontier National Research Council, Division on Earth and Life Studies, Board on Chemical Sciences and Technology, Committee on Challenges for the Chemical Sciences in the 21st Century, 2003-03-19 Chemistry and chemical engineering have changed significantly in the last decade. They have broadened their scopeâ€into biology, nanotechnology, materials science, computation, and advanced methods of process systems engineering and controlâ€so much that the programs in most chemistry and chemical engineering departments now barely resemble the classical notion of chemistry. Beyond the Molecular Frontier brings together research, discovery, and invention across the entire spectrum of the chemical sciencesâ€from fundamental, molecular-level chemistry to large-scale chemical processing technology. This reflects the way the field has evolved, the synergy at universities between research and education in chemistry and chemical engineering, and the way chemists and chemical engineers work together in industry. The astonishing developments in science and engineering during the 20th century have made it possible to dream of new goals that might previously have been considered unthinkable. This book identifies the key opportunities and challenges for the chemical sciences, from basic research to societal needs and from terrorism defense to environmental protection, and it looks at the ways in which chemists and chemical engineers can work together to contribute to an improved future. |
| computer in biology and medicine: Systems Biology Edda Klipp, Wolfram Liebermeister, Christoph Wierling, Axel Kowald, 2016-03-28 This advanced textbook is tailored for an introductory course in Systems Biology and is well-suited for biologists as well as engineers and computer scientists. It comes with student-friendly reading lists and a companion website featuring a short exam prep version of the book and educational modeling programs. The text is written in an easily accessible style and includes numerous worked examples and study questions in each chapter. For this edition, a section on medical systems biology has been included. |
| computer in biology and medicine: Molecular Biology - Not Only for Bioinformaticians Wiesława Widłak, 2013-12-05 Bioinformatics, which can be defined as the application of computer science and information technology to the field of biology and medicine, has been rapidly developing over the past few decades. It generates new knowledge as well as the computational tools to create that knowledge. Understanding the basic processes in living organisms is therefore indispensable for bioinformaticians. This book addresses beginners in molecular biology, especially computer scientists who would like to work as bioinformaticians. It presents basic processes in living organisms in a condensed manner. Additionally, principles of several high-throughput technologies in molecular biology, which need the assistance of bioinformaticians, are explained from a biological point of view. It is structured in the following 9 chapters: cells and viruses; protein structure and function; nucleic acids; DNA replication, mutations, and repair; transcription and posttranscriptional processes; synthesis and posttranslational modifications of proteins; cell division; cell signaling pathways; and high-throughput technologies in molecular biology. |
| computer in biology and medicine: Automated Reasoning for Systems Biology and Medicine Pietro Liò, Paolo Zuliani, 2019-06-11 This book presents outstanding contributions in an exciting, new and multidisciplinary research area: the application of formal, automated reasoning techniques to analyse complex models in systems biology and systems medicine. Automated reasoning is a field of computer science devoted to the development of algorithms that yield trustworthy answers, providing a basis of sound logical reasoning. For example, in the semiconductor industry formal verification is instrumental to ensuring that chip designs are free of defects (or “bugs”). Over the past 15 years, systems biology and systems medicine have been introduced in an attempt to understand the enormous complexity of life from a computational point of view. This has generated a wealth of new knowledge in the form of computational models, whose staggering complexity makes manual analysis methods infeasible. Sound, trusted, and automated means of analysing the models are thus required in order to be able to trust their conclusions. Above all, this is crucial to engineering safe biomedical devices and to reducing our reliance on wet-lab experiments and clinical trials, which will in turn produce lower economic and societal costs. Some examples of the questions addressed here include: Can we automatically adjust medications for patients with multiple chronic conditions? Can we verify that an artificial pancreas system delivers insulin in a way that ensures Type 1 diabetic patients never suffer from hyperglycaemia or hypoglycaemia? And lastly, can we predict what kind of mutations a cancer cell is likely to undergo? This book brings together leading researchers from a number of highly interdisciplinary areas, including: · Parameter inference from time series · Model selection · Network structure identification · Machine learning · Systems medicine · Hypothesis generation from experimental data · Systems biology, systems medicine, and digital pathology · Verification of biomedical devices “This book presents a comprehensive spectrum of model-focused analysis techniques for biological systems ...an essential resource for tracking the developments of a fast moving field that promises to revolutionize biology and medicine by the automated analysis of models and data.”Prof Luca Cardelli FRS, University of Oxford |
| computer in biology and medicine: Plasma Medicine M. Laroussi, 2012-05-24 The first book dedicated exclusively to plasma medicine for graduate students and researchers in physics, engineering, biology, medicine and biochemistry. |
| computer in biology and medicine: Topic Detection and Tracking James Allan, 2012-12-06 Topic Detection and Tracking: Event-based Information Organization brings together in one place state-of-the-art research in Topic Detection and Tracking (TDT). This collection of technical papers from leading researchers in the field not only provides several chapters devoted to the research program and its evaluation paradigm, but also presents the most current research results and describes some of the remaining open challenges. Topic Detection and Tracking: Event-based Information Organization is an excellent reference for researchers and practitioners in a variety of fields related to TDT, including information retrieval, automatic speech recognition, machine learning, and information extraction. |
| computer in biology and medicine: Computational Genomics with R Altuna Akalin, 2020-12-16 Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015. |
| computer in biology and medicine: Catalyzing Inquiry at the Interface of Computing and Biology National Research Council, Division on Engineering and Physical Sciences, Computer Science and Telecommunications Board, Committee on Frontiers at the Interface of Computing and Biology, 2006-01-01 Advances in computer science and technology and in biology over the last several years have opened up the possibility for computing to help answer fundamental questions in biology and for biology to help with new approaches to computing. Making the most of the research opportunities at the interface of computing and biology requires the active participation of people from both fields. While past attempts have been made in this direction, circumstances today appear to be much more favorable for progress. To help take advantage of these opportunities, this study was requested of the NRC by the National Science Foundation, the Department of Defense, the National Institutes of Health, and the Department of Energy. The report provides the basis for establishing cross-disciplinary collaboration between biology and computing including an analysis of potential impediments and strategies for overcoming them. The report also presents a wealth of examples that should encourage students in the biological sciences to look for ways to enable them to be more effective users of computing in their studies. |
| computer in biology and medicine: Encyclopedia of Bioinformatics and Computational Biology , 2018-08-21 Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics, Three Volume Set combines elements of computer science, information technology, mathematics, statistics and biotechnology, providing the methodology and in silico solutions to mine biological data and processes. The book covers Theory, Topics and Applications, with a special focus on Integrative –omics and Systems Biology. The theoretical, methodological underpinnings of BCB, including phylogeny are covered, as are more current areas of focus, such as translational bioinformatics, cheminformatics, and environmental informatics. Finally, Applications provide guidance for commonly asked questions. This major reference work spans basic and cutting-edge methodologies authored by leaders in the field, providing an invaluable resource for students, scientists, professionals in research institutes, and a broad swath of researchers in biotechnology and the biomedical and pharmaceutical industries. Brings together information from computer science, information technology, mathematics, statistics and biotechnology Written and reviewed by leading experts in the field, providing a unique and authoritative resource Focuses on the main theoretical and methodological concepts before expanding on specific topics and applications Includes interactive images, multimedia tools and crosslinking to further resources and databases |
| computer in biology and medicine: Bioinformatics and Computational Biology Basant K. Tiwary, 2021-11-23 This textbook introduces fundamental concepts of bioinformatics and computational biology to the students and researchers in biology, medicine, veterinary science, agriculture, and bioengineering . The respective chapters provide detailed information on biological databases, sequence alignment, molecular evolution, next-generation sequencing, systems biology, and statistical computing using R. The book also presents a case-based discussion on clinical, veterinary, agricultural bioinformatics, and computational bioengineering for application-based learning in the respective fields. Further, it offers readers guidance on reconstructing and analysing biological networks and highlights computational methods used in systems medicine and genome-wide association mapping of diseases. Given its scope, this textbook offers an essential introductory book on bioinformatics and computational biology for undergraduate and graduate students in the life sciences, botany, zoology, physiology, biotechnology, bioinformatics, and genomic science as well as systems biology, bioengineering and the agricultural, and veterinary sciences. |
| computer in biology and medicine: Methods in Medical Informatics Jules J. Berman, 2010-09-22 Too often, healthcare workers are led to believe that medical informatics is a complex field that can only be mastered by teams of professional programmers. This is simply not the case. With just a few dozen simple algorithms, easily implemented with open source programming languages, you can fully utilize the medical information contained in clini |
| computer in biology and medicine: Data Acquisition and Processing in Biology and Medicine Kurt Enslein, 1962 |
| computer in biology and medicine: Modeling in Systems Biology Ina Koch, Wolfgang Reisig, Falk Schreiber, 2010-10-21 The emerging, multi-disciplinary field of systems biology is devoted to the study of the relationships between various parts of a biological system, and computer modeling plays a vital role in the drive to understand the processes of life from an holistic viewpoint. Advancements in experimental technologies in biology and medicine have generated an enormous amount of biological data on the dependencies and interactions of many different molecular cell processes, fueling the development of numerous computational methods for exploring this data. The mathematical formalism of Petri net theory is able to encompass many of these techniques. This essential text/reference presents a comprehensive overview of cutting-edge research in applications of Petri nets in systems biology, with contributions from an international selection of experts. Those unfamiliar with the field are also provided with a general introduction to systems biology, the foundations of biochemistry, and the basics of Petri net theory. Further chapters address Petri net modeling techniques for building and analyzing biological models, as well as network prediction approaches, before reviewing the applications to networks of different biological classification. Topics and features: investigates the modular, qualitative modeling of regulatory networks using Petri nets, and examines an Hybrid Functional Petri net simulation case study; contains a glossary of the concepts and notation used in the book, in addition to exercises at the end of each chapter; covers the topological analysis of metabolic and regulatory networks, the analysis of models of signaling networks, and the prediction of network structure; provides a biological case study on the conversion of logical networks into Petri nets; discusses discrete modeling, stochastic modeling, fuzzy modeling, dynamic pathway modeling, genetic regulatory network modeling, and quantitative analysis techniques; includes a Foreword by Professor Jens Reich, Professor of Bioinformatics at Humboldt University and Max Delbrück Center for Molecular Medicine in Berlin. This unique guide to the modeling of biochemical systems using Petri net concepts will be of real utility to researchers and students of computational biology, systems biology, bioinformatics, computer science, and biochemistry. |
| computer in biology and medicine: Deep Learning for the Life Sciences Bharath Ramsundar, Peter Eastman, Patrick Walters, Vijay Pande, 2019-04-10 Deep learning has already achieved remarkable results in many fields. Now it’s making waves throughout the sciences broadly and the life sciences in particular. This practical book teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics, microscopy, medical analysis, and other fields. Ideal for practicing developers and scientists ready to apply their skills to scientific applications such as biology, genetics, and drug discovery, this book introduces several deep network primitives. You’ll follow a case study on the problem of designing new therapeutics that ties together physics, chemistry, biology, and medicine—an example that represents one of science’s greatest challenges. Learn the basics of performing machine learning on molecular data Understand why deep learning is a powerful tool for genetics and genomics Apply deep learning to understand biophysical systems Get a brief introduction to machine learning with DeepChem Use deep learning to analyze microscopic images Analyze medical scans using deep learning techniques Learn about variational autoencoders and generative adversarial networks Interpret what your model is doing and how it’s working |
| computer in biology and medicine: Modeling and Simulation in Medicine and the Life Sciences Frank C. Hoppensteadt, Charles S. Peskin, 2012-12-06 The result of lectures given by the authors at New York University, the University of Utah, and Michigan State University, the material is written for students who have had only one term of calculus, but it contains material that can be used in modeling courses in applied mathematics at all levels through early graduate courses. Numerous exercises are given as well as solutions to selected exercises, so as to lead readers to discover interesting extensions of that material. Throughout, illustrations depict physiological processes, population biology phenomena, corresponding models, and the results of computer simulations. Topics covered range from population phenomena to demographics, genetics, epidemics and dispersal; in physiological processes, including the circulation, gas exchange in the lungs, control of cell volume, the renal counter-current multiplier mechanism, and muscle mechanics; to mechanisms of neural control. Each chapter is graded in difficulty, so a reading of the first parts of each provides an elementary introduction to the processes and their models. |
| computer in biology and medicine: Handbook of Research on Computational and Systems Biology Limin Angela Liu, Dongqing Wei, Yixue Li, 2011 This book offers information on the state-of-the-art development in the fields of computational biology and systems biology, presenting methods, tools, and applications of these fields by many leading experts around the globe--Provided by publisher. |
| computer in biology and medicine: From Systems Biology to Systems Medicine James A. Marcum, 2020-07-09 Throughout most of the twentieth century, the biomedical model dominated healthcare. However, the biomedical model had its critics, who proposed alternative models to replace it. Eventually, biomedicine became fragmented at its foundations with a variety of approaches to its nature and practice. Medicine's current response to this fragmentation is to combine these disparate approaches into a single system--systems medicine. In the present book, I examine the shift, during the postgenomics era, from the biomedical model to systems medicine vis-à-vis systems biology, as well as the challenges facing systems medicine's implementation in the twenty-first century. The main goal of the present book is to provide a disciplinary framework for examining the rise of systems medicine, especially in terms of the incorporation of systems biology into the biomedical model. To realize that goal, the following questions are addressed. What is a disciplinary framework? And, why is this framework important for understanding systems biology and medicine? Briefly, a disciplinary framework represents the relational structure among disparate disciplines that support and ground a discipline and its corpus. For traditional biology and medicine, that framework consists of various disciplines within the biological and biomedical sciences, including physiology, neuroscience, pathology, and epidemiology--to name a few. For the present purpose, systems biology within the last several decades is reshaping the disciplinary framework of the biological and biomedical sciences, which is also responsible for the emergence of systems medicine. In addition, the challenges facing systems medicine, especially its operationalization and implementation with respect to medical education and practice, as well as research, are also explored. |
| computer in biology and medicine: Biomedical Platforms Peter Keating, Alberto Cambrosio, 2003 An examination of postwar medicine based on the notion of the biomedical platform--the theoretical and clinical meeting ground between the normal and the pathological. |
| computer in biology and medicine: Methods in Computational Biology Ross Carlson, Herbert Sauro, 2019-07-03 Modern biology is rapidly becoming a study of large sets of data. Understanding these data sets is a major challenge for most life sciences, including the medical, environmental, and bioprocess fields. Computational biology approaches are essential for leveraging this ongoing revolution in omics data. A primary goal of this Special Issue, entitled “Methods in Computational Biology”, is the communication of computational biology methods, which can extract biological design principles from complex data sets, described in enough detail to permit the reproduction of the results. This issue integrates interdisciplinary researchers such as biologists, computer scientists, engineers, and mathematicians to advance biological systems analysis. The Special Issue contains the following sections: • Reviews of Computational Methods • Computational Analysis of Biological Dynamics: From Molecular to Cellular to Tissue/Consortia Levels • The Interface of Biotic and Abiotic Processes • Processing of Large Data Sets for Enhanced Analysis • Parameter Optimization and Measurement |
| computer in biology and medicine: Deep Learning in Biology and Medicine Davide Bacciu, Paulo J. G. Lisboa, Alfredo Vellido, 2021 Biology, medicine and biochemistry have become data-centric fields for which Deep Learning methods are delivering groundbreaking results. Addressing high impact challenges, Deep Learning in Biology and Medicine provides an accessible and organic collection of Deep Learning essays on bioinformatics and medicine. It caters for a wide readership, ranging from machine learning practitioners and data scientists seeking methodological knowledge to address biomedical applications, to life science specialists in search of a gentle reference for advanced data analytics.With contributions from internationally renowned experts, the book covers foundational methodologies in a wide spectrum of life sciences applications, including electronic health record processing, diagnostic imaging, text processing, as well as omics-data processing. This survey of consolidated problems is complemented by a selection of advanced applications, including cheminformatics and biomedical interaction network analysis. A modern and mindful approach to the use of data-driven methodologies in the life sciences also requires careful consideration of the associated societal, ethical, legal and transparency challenges, which are covered in the concluding chapters of this book. |
| computer in biology and medicine: Bioinformatics and Computational Biology Hamid R. Arabnia, Fernando G. Tinetti, Quoc-Nam Tran, 2020-03-13 Proceedings of the 2019 International Conference on Bioinformatics & Computational Biology (BIOCOMP'19) held July 29th - August 1st, 2019 in Las Vegas, Nevada. |
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Computers in Biology and Medicine 183 (2024) 109303 Available online 28 October 2024 0010-4825/© 2024 Published by Elsevier Ltd. 1. Introduction Mild cognitive impairment (MCI) is a …
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cDepartment of Biochemistry and Molecular Biology, Michigan State University, MI, 48824, USA dDepartment of Electrical and Computer Engineering, Michigan State University, MI, 48824, …
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c Division of Gastroenterology and Hepatology, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA ARTICLE INFO Keywords: Esophagus Stomach …
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cDepartment of Biochemistry and Molecular Biology, Michigan State University, MI, 48824, USA dDepartment of Electrical and Computer Engineering, Michigan State University, MI, 48824, …
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164 C.N. Devi et al. / Computers in Biology and Medicine 64 (2015) 163–178. 2.2. Neonatal brain visualization by MRI Usually, a combination of T1 and T2 weighted images is used to
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c School of Computer Science and Engineering, Inha University, Republic of Korea d School of Cmputer Sience and Technology, Wuhan University of Science and Technology, Wuhan, …
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dDepartment of Computer Science, Vanderbilt University, Nashville, TN, USA eDepartment of Radiology, Weill Cornell Medicine, New York, USA ARTICLE INFO Keywords: PubMed Articial …
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b Department of Medicine, Division of Infectious Diseases and International Health, University of Virginia, Charlottesville, VA, 22908, USA c Department of Defense Biotechnology High …
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d Department of Software Engineering and Computer Science, Riphah International University, Gulberg Green Campus Islamabad, Pakistan ARTICLE INFO Keywords: Attention mechanism …
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DNA data storage is a promising technology that utilizes computer simulation, and synthetic biology, offering high-density and reliable digital information storage. It is challenging to store ...
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b Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University Technology, Delft, the Netherlands ARTICLE INFO Keywords: Atrial fibrillation ECG signal …
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Computers in Biology and Medicine 89 (2017) 68–75 Downloaded for Anonymous User (n/a) at Drexel University from ClinicalKey.com by Elsevier on December 19, 2023.
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cDepartment of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA dMedical Physics Unit, Cannizzaro Hospital, Catania, Italy eNuclear Medicine …
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Computers in Biology and Medicine 72 (2016) 226–228. automatic infection detection from urinoculture Petri dish image analysis [4]. The increasing role of computational intelligence has …
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Machine learning classification of medication adherence in patients with movement disorders using non-wearable sensors Conrad Tuckera,b,n, Ishan Behoorab, Harriet Black Nembhardc, …
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aChapman University, Schmid College of Science and Technology, Mathematics and Computer Science, Orange, CA, 92866, USA b Chapman University, School of Pharmacy, Department of …
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Computers in Biology and Medicine 43 (2013) 1098–1113. plaque precursors. Forces exerted by the flowing blood on the endothelium may be decomposed into two perpendicular compo …
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a Department of Biology, Carleton University, Ottawa, Canada b School of Computer Science, Carleton University, Ottawa, Canada c Department of Systems and Computer Engineering, …
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a Computer Science and Engineering, Northeastern University, Shenyang, China b Key Laboratory of Intelligent Computing in Medical Image Ministry Education, Northeastern …
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Computers in Biology and Medicine 64 (2015) 101–116. Proenca et al. [2] developed a fully automatic technique to detect virus particles in transmission electron microscopy images
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processing from the perspective of Computer Vision. As first contribution we present a survey of the ... Computers in Biology and Medicine 77 (2016) 23–39. of images collected through the …
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ventilator cycling asynchrony using machine learning, Computers in Biology and Medicine (2018), doi: 10.1016/j.compbiomed.2018.04.016. This is a PDF file of an unedited manuscript that has …
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Computer-aided diagnosis ABSTRACT Deep learning architecture with convolutional neural network (CNN) achieves outstanding success in the field of computer vision. Where U-Net, an …
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Computer tomography (CT) Mass–spring models Spline curves Image features abstract We propose a computer-aided detection (CAD) system which can detect small-sized (from 3 mm) …
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Automated beat‐wise arrhythmia diagnosis using modified U‐net on extended electrocardiographic recordings with heterogeneous arrhythmia types Shu Lih Oh a, Eddie Y K Ng b, Ru‐San Tan c, …
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Computers in Biology and Medicine 51 (2014) 140–158. with the Brazilian population estimated a prevalence of dementia of 8% for the elderly population [6]. The screening tools, assess-ment …
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arXiv:2112.00760v2 [quant-ph] 16 Dec 2021
Biology and Medicine in the Landscape of Quantum Advantages Benjamin A. Cordier1, Nicolas P. D. Sawaya2, Gian Giacomo Guerreschi2, Shannon K. McWeeney1,3,4 1 Department of …
