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| computer science with specialization in bioinformatics: Bioinformatics Algorithms Phillip Compeau, Pavel Pevzner, 1986-06 Bioinformatics Algorithms: an Active Learning Approach is one of the first textbooks to emerge from the recent Massive Online Open Course (MOOC) revolution. A light-hearted and analogy-filled companion to the authors' acclaimed online course (http://coursera.org/course/bioinformatics), this book presents students with a dynamic approach to learning bioinformatics. It strikes a unique balance between practical challenges in modern biology and fundamental algorithmic ideas, thus capturing the interest of students of biology and computer science students alike.Each chapter begins with a central biological question, such as Are There Fragile Regions in the Human Genome? or Which DNA Patterns Play the Role of Molecular Clocks? and then steadily develops the algorithmic sophistication required to answer this question. Hundreds of exercises are incorporated directly into the text as soon as they are needed; readers can test their knowledge through automated coding challenges on Rosalind (http://rosalind.info), an online platform for learning bioinformatics.The textbook website (http://bioinformaticsalgorithms.org) directs readers toward additional educational materials, including video lectures and PowerPoint slides. |
| computer science with specialization in bioinformatics: Applied Bioinformatics Paul Maria Selzer, Richard Marhöfer, Andreas Rohwer, 2008-01-18 At last, here is a baseline book for anyone who is confused by cryptic computer programs, algorithms and formulae, but wants to learn about applied bioinformatics. Now, anyone who can operate a PC, standard software and the internet can also learn to understand the biological basis of bioinformatics, of the existence as well as the source and availability of bioinformatics software, and how to apply these tools and interpret results with confidence. This process is aided by chapters that introduce important aspects of bioinformatics, detailed bioinformatics exercises (including solutions), and to cap it all, a glossary of definitions and terminology relating to bioinformatics. |
| computer science with specialization in bioinformatics: Bioinformatics and Biomedical Engineering Ignacio Rojas, Francisco Ortuño, 2018-04-19 This two-volume set LNBI 10813 and LNBI 10814 constitutes the proceedings of the 6th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2018, held in Granada, Spain, in April 2018.The 88 regular papers presented were carefully reviewed and selected from 273 submissions. The scope of the conference spans the following areas: bioinformatics for healthcare and diseases; bioinformatics tools to integrate omics dataset and address biological question; challenges and advances in measurement and self-parametrization of complex biological systems; computational genomics; computational proteomics; computational systems for modelling biological processes; drug delivery system design aided by mathematical modelling and experiments; generation, management and biological insights from big data; high-throughput bioinformatic tools for medical genomics; next generation sequencing and sequence analysis; interpretable models in biomedicine and bioinformatics; little-big data. Reducing the complexity and facing uncertainty of highly underdetermined phenotype prediction problems; biomedical engineering; biomedical image analysis; biomedical signal analysis; challenges in smart and wearable sensor design for mobile health; and healthcare and diseases. |
| computer science with specialization in bioinformatics: Schedule of Classes University of California, San Diego, 2003 |
| computer science with specialization in bioinformatics: Algorithms in Bioinformatics Wing-Kin Sung, 2009-11-24 Thoroughly Describes Biological Applications, Computational Problems, and Various Algorithmic Solutions Developed from the author's own teaching material, Algorithms in Bioinformatics: A Practical Introduction provides an in-depth introduction to the algorithmic techniques applied in bioinformatics. For each topic, the author clearly details the bi |
| computer science with specialization in bioinformatics: Practical Bioinformatics Janusz M. Bujnicki, 2004-03-03 Bridges the gap between bioinformaticists and molecular biologists, i.e. the developers and the users of computational methods for biological data analysis and in that it presents examples of practical applications of the bioinformatics tools in the daily practice of an experimental research scientist. |
| computer science with specialization in bioinformatics: Peterson's Graduate Programs in Engineering & Applied Sciences 2012 Peterson's, 2012-03-09 Peterson's Graduate Programs in Engineering & Applied Sciences 2012 contains a wealth of information on accredited institutions offering graduate degree programs in these fields. Up-to-date data, collected through Peterson's Annual Survey of Graduate and Professional Institutions, provides valuable information on degree offerings, professional accreditation, jointly offered degrees, part-time and evening/weekend programs, postbaccalaureate distance degrees, faculty, students, requirements, expenses, financial support, faculty research, and unit head and application contact information. There are helpful links to in-depth descriptions about a specific graduate program or department, faculty members and their research, and more. There are also valuable articles on financial assistance, the graduate admissions process, advice for international and minority students, and facts about accreditation, with a current list of accrediting agencies. |
| computer science with specialization in bioinformatics: Translational Biomedical Informatics Bairong Shen, Haixu Tang, Xiaoqian Jiang, 2016-10-31 This book introduces readers to essential methods and applications in translational biomedical informatics, which include biomedical big data, cloud computing and algorithms for understanding omics data, imaging data, electronic health records and public health data. The storage, retrieval, mining and knowledge discovery of biomedical big data will be among the key challenges for future translational research. The paradigm for precision medicine and healthcare needs to integratively analyze not only the data at the same level – e.g. different omics data at the molecular level – but also data from different levels – the molecular, cellular, tissue, clinical and public health level. This book discusses the following major aspects: the structure of cross-level data; clinical patient information and its shareability; and standardization and privacy. It offers a valuable guide for all biologists, biomedical informaticians and clinicians with an interest in Precision Medicine Informatics. |
| computer science with specialization in bioinformatics: Systems Biology: A Very Short Introduction Eberhard O. Voit, 2020-03-26 Systems biology came about as growing numbers of engineers and scientists from other fields created algorithms which supported the analysis of biological data in incredible quantities. Whereas biologists of the past had been forced to study one item or aspect at a time, due to technical and biological limitations, it suddenly became possible to study biological phenomena within their natural contexts. This interdisciplinary field offers a holistic approach to interpreting these processes, and has been responsible for some of the most important developments in the science of human health and environmental sustainability. This Very Short Introduction outlines the exciting processes and possibilities in the new field of systems biology. Eberhard O. Voit describes how it enabled us to learn how intricately the expression of every gene is controlled, how signaling systems keep organisms running smoothly, and how complicated even the simplest cells are. He explores what this field is about, why it is needed, and how it will affect our understanding of life, particularly in the areas of personalized medicine, drug development, food and energy production, and sustainable stewardship of our environments. Throughout he considers how new tools are being provided from the fields of mathematics, computer science, engineering, physics, and chemistry to grasp the complexity of the countless interacting processes in cells which would overwhelm the cognitive and analytical capabilities of the human mind. ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable. |
| computer science with specialization in bioinformatics: Creative Minds, Charmed Lives Yu Kiang Leong, 2010 This book features interviews of 38 eminent mathematicians and mathematical scientists who were invited to participate in the programs of the Institute for Mathematical Sciences, National University of Singapore. Originally published in its newsletter Imprints from 2003 to 2009, these interviews give a fascinating and insightful glimpse into the passion driving some of the most creative minds in modern research in pure mathematics, applied mathematics, statistics, economics and engineering. The reader is drawn into a panorama of the past and present development of some of the ideas that have revolutionized modern science and mathematics. This book should be relevant to those who are interested in the history and psychology of ideas. It should provide motivation, inspiration and guidance to students who aspire to do research and to beginning researchers who are looking for career niches. For those who wish to be broadly educated, it is informative without delving into excessive technical details and is, at the same time, thought provoking enough to arouse their curiosity to learn more about the world around them. |
| computer science with specialization in bioinformatics: Supercomputing Vladimir Voevodin, Sergey Sobolev, 2019-12-09 This book constitutes the refereed post-conference proceedings of the 5th Russian Supercomputing Days, RuSCDays 2019, held in Moscow, Russia, in September 2019. The 60 revised full papers presented were carefully reviewed and selected from 127 submissions. The papers are organized in the following topical sections: parallel algorithms; supercomputer simulation; HPC, BigData, AI: architectures, technologies, tools; and distributed and cloud computing. |
| computer science with specialization in bioinformatics: Introduction to Genomics Arthur Lesk, 2012 This book covers the latest techniques that enable us to study the genome in detail, the book explores what the genome tells us about life at the level of the molecule, the cell, and the organism |
| computer science with specialization in bioinformatics: Quick Reference for Counselors , 2009 |
| computer science with specialization in bioinformatics: Internet of Things (IoT) BK Tripathy, J Anuradha, 2017-10-10 The term IoT, which was first proposed by Kevin Ashton, a British technologist, in 1999 has the potential to impact everything from new product opportunities to shop floor optimization to factory worker efficiency gains, that will power top-line and bottom-line gains. As IoT technology is being put to diversified use, the current technology needs to be improved to enhance privacy and built secure devices by adopting a security-focused approach, reducing the amount of data collected, increasing transparency and providing consumers with a choice to opt out. Therefore, the current volume has been compiled, in an effort to draw the various issues in IoT, challenges faced and existing solutions so far. Key Points: • Provides an overview of basic concepts and technologies of IoT with communication technologies ranging from 4G to 5G and its architecture. • Discusses recent security and privacy studies and social behavior of human beings over IoT. • Covers the issues related to sensors, business model, principles, paradigms, green IoT and solutions to handle relevant challenges. • Presents the readers with practical ideas of using IoT, how it deals with human dynamics, the ecosystem, the social objects and their relation. • Deals with the challenges involved in surpassing diversified architecture, protocol, communications, integrity and security. |
| computer science with specialization in bioinformatics: Lewin's GENES X Benjamin Lewin, Jocelyn Krebs, Stephen T. Kilpatrick, Elliott S. Goldstein, 2011 Jacket. |
| computer science with specialization in bioinformatics: Bioconductor Case Studies Florian Hahne, Wolfgang Huber, Robert Gentleman, Seth Falcon, 2010-06-09 Bioconductor software has become a standard tool for the analysis and comprehension of data from high-throughput genomics experiments. Its application spans a broad field of technologies used in contemporary molecular biology. In this volume, the authors present a collection of cases to apply Bioconductor tools in the analysis of microarray gene expression data. Topics covered include: (1) import and preprocessing of data from various sources; (2) statistical modeling of differential gene expression; (3) biological metadata; (4) application of graphs and graph rendering; (5) machine learning for clustering and classification problems; (6) gene set enrichment analysis. Each chapter of this book describes an analysis of real data using hands-on example driven approaches. Short exercises help in the learning process and invite more advanced considerations of key topics. The book is a dynamic document. All the code shown can be executed on a local computer, and readers are able to reproduce every computation, figure, and table. |
| computer science with specialization in bioinformatics: Post-genome Informatics 實·金久, 2000-01 Blueprint of life. Molecular biology databases. Sequence analysis of nucleic acids and proteins. Network analysis of molecular interactions. |
| computer science with specialization in bioinformatics: Assessing and Responding to the Growth of Computer Science Undergraduate Enrollments National Academies of Sciences, Engineering, and Medicine, Division on Engineering and Physical Sciences, Computer Science and Telecommunications Board, Policy and Global Affairs, Board on Higher Education and Workforce, Committee on the Growth of Computer Science Undergraduate Enrollments, 2018-04-28 The field of computer science (CS) is currently experiencing a surge in undergraduate degree production and course enrollments, which is straining program resources at many institutions and causing concern among faculty and administrators about how best to respond to the rapidly growing demand. There is also significant interest about what this growth will mean for the future of CS programs, the role of computer science in academic institutions, the field as a whole, and U.S. society more broadly. Assessing and Responding to the Growth of Computer Science Undergraduate Enrollments seeks to provide a better understanding of the current trends in computing enrollments in the context of past trends. It examines drivers of the current enrollment surge, relationships between the surge and current and potential gains in diversity in the field, and the potential impacts of responses to the increased demand for computing in higher education, and it considers the likely effects of those responses on students, faculty, and institutions. This report provides recommendations for what institutions of higher education, government agencies, and the private sector can do to respond to the surge and plan for a strong and sustainable future for the field of CS in general, the health of the institutions of higher education, and the prosperity of the nation. |
| computer science with specialization in bioinformatics: Methodologies and Applications of Computational Statistics for Machine Intelligence Samanta, Debabrata, Rao Althar, Raghavendra, Pramanik, Sabyasachi, Dutta, Soumi, 2021-06-25 With the field of computational statistics growing rapidly, there is a need for capturing the advances and assessing their impact. Advances in simulation and graphical analysis also add to the pace of the statistical analytics field. Computational statistics play a key role in financial applications, particularly risk management and derivative pricing, biological applications including bioinformatics and computational biology, and computer network security applications that touch the lives of people. With high impacting areas such as these, it becomes important to dig deeper into the subject and explore the key areas and their progress in the recent past. Methodologies and Applications of Computational Statistics for Machine Intelligence serves as a guide to the applications of new advances in computational statistics. This text holds an accumulation of the thoughts of multiple experts together, keeping the focus on core computational statistics that apply to all domains. Covering topics including artificial intelligence, deep learning, and trend analysis, this book is an ideal resource for statisticians, computer scientists, mathematicians, lecturers, tutors, researchers, academic and corporate libraries, practitioners, professionals, students, and academicians. |
| computer science with specialization in bioinformatics: Peterson's Graduate Programs in Computer Science & Information Technology, Electrical & Computer Engineering, and Energy & Power Engineering 2011 Peterson's, 2011-05-01 Peterson's Graduate Programs in Computer Science & Information Technology, Electrical & Computer Engineering, and Energy & Power Engineering contains a wealth of information on colleges and universities that offer graduate work these exciting fields. The profiled institutions include those in the United States, Canada and abroad that are accredited by U.S. accrediting bodies. Up-to-date data, collected through Peterson's Annual Survey of Graduate and Professional Institutions, provides valuable information on degree offerings, professional accreditation, jointly offered degrees, part-time and evening/weekend programs, postbaccalaureate distance degrees, faculty, students, degree requirements, entrance requirements, expenses, financial support, faculty research, and unit head and application contact information. Readers will find helpful links to in-depth descriptions that offer additional detailed information about a specific program or department, faculty members and their research, and much more. In addition, there are valuable articles on financial assistance, the graduate admissions process, advice for international and minority students, and facts about accreditation, with a current list of accrediting agencies. |
| computer science with specialization in bioinformatics: Bioinformatics in Agriculture Pradeep Sharma, Dinesh Yadav, R.K. Gaur, 2022-04-28 Bioinformatics in Agriculture: Next Generation Sequencing Era is a comprehensive volume presenting an integrated research and development approach to the practical application of genomics to improve agricultural crops. Exploring both the theoretical and applied aspects of computational biology, and focusing on the innovation processes, the book highlights the increased productivity of a translational approach. Presented in four sections and including insights from experts from around the world, the book includes: Section I: Bioinformatics and Next Generation Sequencing Technologies; Section II: Omics Application; Section III: Data mining and Markers Discovery; Section IV: Artificial Intelligence and Agribots. Bioinformatics in Agriculture: Next Generation Sequencing Era explores deep sequencing, NGS, genomic, transcriptome analysis and multiplexing, highlighting practices forreducing time, cost, and effort for the analysis of gene as they are pooled, and sequenced. Readers will gain real-world information on computational biology, genomics, applied data mining, machine learning, and artificial intelligence. This book serves as a complete package for advanced undergraduate students, researchers, and scientists with an interest in bioinformatics. - Discusses integral aspects of molecular biology and pivotal tool sfor molecular breeding - Enables breeders to design cost-effective and efficient breeding strategies - Provides examples ofinnovative genome-wide marker (SSR, SNP) discovery - Explores both the theoretical and practical aspects of computational biology with focus on innovation processes - Covers recent trends of bioinformatics and different tools and techniques |
| computer science with specialization in bioinformatics: Practical Bioinformatics Michael Agostino, 2012-09-26 Practical Bioinformatics is specifically designed for biology majors, with a heavy emphasis on the steps required to perform bioinformatics analysis to answer biological questions. It is written for courses that have a practical, hands-on element and contains many exercises (for example, database searches, protein analysis, data interpretation) to |
| computer science with specialization in bioinformatics: Introduction to Computational Genomics Nello Cristianini, Matthew W. Hahn, 2006-12-14 Where did SARS come from? Have we inherited genes from Neanderthals? How do plants use their internal clock? The genomic revolution in biology enables us to answer such questions. But the revolution would have been impossible without the support of powerful computational and statistical methods that enable us to exploit genomic data. Many universities are introducing courses to train the next generation of bioinformaticians: biologists fluent in mathematics and computer science, and data analysts familiar with biology. This readable and entertaining book, based on successful taught courses, provides a roadmap to navigate entry to this field. It guides the reader through key achievements of bioinformatics, using a hands-on approach. Statistical sequence analysis, sequence alignment, hidden Markov models, gene and motif finding and more, are introduced in a rigorous yet accessible way. A companion website provides the reader with Matlab-related software tools for reproducing the steps demonstrated in the book. |
| computer science with specialization in bioinformatics: Essential Bioinformatics Jin Xiong, 2006-03-13 Essential Bioinformatics is a concise yet comprehensive textbook of bioinformatics, which provides a broad introduction to the entire field. Written specifically for a life science audience, the basics of bioinformatics are explained, followed by discussions of the state-of-the-art computational tools available to solve biological research problems. All key areas of bioinformatics are covered including biological databases, sequence alignment, genes and promoter prediction, molecular phylogenetics, structural bioinformatics, genomics and proteomics. The book emphasizes how computational methods work and compares the strengths and weaknesses of different methods. This balanced yet easily accessible text will be invaluable to students who do not have sophisticated computational backgrounds. Technical details of computational algorithms are explained with a minimum use of mathematical formulae; graphical illustrations are used in their place to aid understanding. The effective synthesis of existing literature as well as in-depth and up-to-date coverage of all key topics in bioinformatics make this an ideal textbook for all bioinformatics courses taken by life science students and for researchers wishing to develop their knowledge of bioinformatics to facilitate their own research. |
| computer science with specialization in bioinformatics: Computational Science - ICCS 2006 , 2006 |
| computer science with specialization in bioinformatics: Statistical Methods in Bioinformatics Warren J. Ewens, Gregory R. Grant, 2005-09-30 Advances in computers and biotechnology have had a profound impact on biomedical research, and as a result complex data sets can now be generated to address extremely complex biological questions. Correspondingly, advances in the statistical methods necessary to analyze such data are following closely behind the advances in data generation methods. The statistical methods required by bioinformatics present many new and difficult problems for the research community. This book provides an introduction to some of these new methods. The main biological topics treated include sequence analysis, BLAST, microarray analysis, gene finding, and the analysis of evolutionary processes. The main statistical techniques covered include hypothesis testing and estimation, Poisson processes, Markov models and Hidden Markov models, and multiple testing methods. The second edition features new chapters on microarray analysis and on statistical inference, including a discussion of ANOVA, and discussions of the statistical theory of motifs and methods based on the hypergeometric distribution. Much material has been clarified and reorganized. The book is written so as to appeal to biologists and computer scientists who wish to know more about the statistical methods of the field, as well as to trained statisticians who wish to become involved with bioinformatics. The earlier chapters introduce the concepts of probability and statistics at an elementary level, but with an emphasis on material relevant to later chapters and often not covered in standard introductory texts. Later chapters should be immediately accessible to the trained statistician. Sufficient mathematical background consists of introductory courses in calculus and linear algebra. The basic biological concepts that are used are explained, or can be understood from the context, and standard mathematical concepts are summarized in an Appendix. Problems are provided at the end of each chapter allowing the reader to develop aspects of the theory outlined in the main text. Warren J. Ewens holds the Christopher H. Brown Distinguished Professorship at the University of Pennsylvania. He is the author of two books, Population Genetics and Mathematical Population Genetics. He is a senior editor of Annals of Human Genetics and has served on the editorial boards of Theoretical Population Biology, GENETICS, Proceedings of the Royal Society B and SIAM Journal in Mathematical Biology. He is a fellow of the Royal Society and the Australian Academy of Science. Gregory R. Grant is a senior bioinformatics researcher in the University of Pennsylvania Computational Biology and Informatics Laboratory. He obtained his Ph.D. in number theory from the University of Maryland in 1995 and his Masters in Computer Science from the University of Pennsylvania in 1999. Comments on the first edition: This book would be an ideal text for a postgraduate course...[and] is equally well suited to individual study.... I would recommend the book highly. (Biometrics) Ewens and Grant have given us a very welcome introduction to what is behind those pretty [graphical user] interfaces. (Naturwissenschaften) The authors do an excellent job of presenting the essence of the material without getting bogged down in mathematical details. (Journal American Statistical Association) The authors have restructured classical material to a great extent and the new organization of the different topics is one of the outstanding services of the book. (Metrika) |
| computer science with specialization in bioinformatics: Bioinformatics For Dummies Jean-Michel Claverie, Cedric Notredame, 2011-02-10 Were you always curious about biology but were afraid to sit through long hours of dense reading? Did you like the subject when you were in high school but had other plans after you graduated? Now you can explore the human genome and analyze DNA without ever leaving your desktop! Bioinformatics For Dummies is packed with valuable information that introduces you to this exciting new discipline. This easy-to-follow guide leads you step by step through every bioinformatics task that can be done over the Internet. Forget long equations, computer-geek gibberish, and installing bulky programs that slow down your computer. You’ll be amazed at all the things you can accomplish just by logging on and following these trusty directions. You get the tools you need to: Analyze all types of sequences Use all types of databases Work with DNA and protein sequences Conduct similarity searches Build a multiple sequence alignment Edit and publish alignments Visualize protein 3-D structures Construct phylogenetic trees This up-to-date second edition includes newly created and popular databases and Internet programs as well as multiple new genomes. It provides tips for using servers and places to seek resources to find out about what’s going on in the bioinformatics world. Bioinformatics For Dummies will show you how to get the most out of your PC and the right Web tools so you'll be searching databases and analyzing sequences like a pro! |
| computer science with specialization in bioinformatics: Analytics and Knowledge Management Suliman Hawamdeh, Hsia-Ching Chang, 2018-08-06 The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics technique. Analytics and Knowledge Management examines the role of analytics in knowledge management and the integration of big data theories, methods, and techniques into an organizational knowledge management framework. Its chapters written by researchers and professionals provide insight into theories, models, techniques, and applications with case studies examining the use of analytics in organizations. The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics techniques. Analytics, on the other hand, is the examination, interpretation, and discovery of meaningful patterns, trends, and knowledge from data and textual information. It provides the basis for knowledge discovery and completes the cycle in which knowledge management and knowledge utilization happen. Organizations should develop knowledge focuses on data quality, application domain, selecting analytics techniques, and on how to take actions based on patterns and insights derived from analytics. Case studies in the book explore how to perform analytics on social networking and user-based data to develop knowledge. One case explores analyze data from Twitter feeds. Another examines the analysis of data obtained through user feedback. One chapter introduces the definitions and processes of social media analytics from different perspectives as well as focuses on techniques and tools used for social media analytics. Data visualization has a critical role in the advancement of modern data analytics, particularly in the field of business intelligence and analytics. It can guide managers in understanding market trends and customer purchasing patterns over time. The book illustrates various data visualization tools that can support answering different types of business questions to improve profits and customer relationships. This insightful reference concludes with a chapter on the critical issue of cybersecurity. It examines the process of collecting and organizing data as well as reviewing various tools for text analysis and data analytics and discusses dealing with collections of large datasets and a great deal of diverse data types from legacy system to social networks platforms. |
| computer science with specialization in bioinformatics: Python for Bioinformatics Sebastian Bassi, 2017-08-07 In today's data driven biology, programming knowledge is essential in turning ideas into testable hypothesis. Based on the author’s extensive experience, Python for Bioinformatics, Second Edition helps biologists get to grips with the basics of software development. Requiring no prior knowledge of programming-related concepts, the book focuses on the easy-to-use, yet powerful, Python computer language. This new edition is updated throughout to Python 3 and is designed not just to help scientists master the basics, but to do more in less time and in a reproducible way. New developments added in this edition include NoSQL databases, the Anaconda Python distribution, graphical libraries like Bokeh, and the use of Github for collaborative development. |
| computer science with specialization in bioinformatics: ASEE ... Profiles of Engineering & Engineering Technology Colleges , 2007 |
| computer science with specialization in bioinformatics: 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 science with specialization in bioinformatics: Molecular Biotechnology Carolyn A. Dehlinger, 2014-08-28 The only textbook of its kind on the market, Molecular Biotechnology provides a holistic, comprehensive view of molecular biotechnology that makes it ideally suited for undergraduate majors in molecular biotechnology and biomedical sciences. Beginning with the background of this rapidly expanding field, Molecular Biotechnology covers major discoveries, regulation of the biotechnology industry, and significant innovations. A strong emphasis on careers in molecular biotechnology, profiles of major projects and researchers, and expansive discussions of bioethical concerns and current research, all come together to make this text an engaging and highly relevant resource for biotechnology students. |
| computer science with specialization in bioinformatics: Evolution of Translational Omics Institute of Medicine, Board on Health Sciences Policy, Board on Health Care Services, Committee on the Review of Omics-Based Tests for Predicting Patient Outcomes in Clinical Trials, 2012-09-13 Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials. |
| computer science with specialization in bioinformatics: Introduction to Bioinformatics Arthur M. Lesk, 2019 Lesk provides an accessible and thorough introduction to a subject which is becoming a fundamental part of biological science today. The text generates an understanding of the biological background of bioinformatics. |
| computer science with specialization in bioinformatics: The Processes of Life Lawrence E. Hunter, 2012-01-13 A brief and accessible introduction to molecular biology for students and professionals who want to understand this rapidly expanding field. Recent research in molecular biology has produced a remarkably detailed understanding of how living things operate. Becoming conversant with the intricacies of molecular biology and its extensive technical vocabulary can be a challenge, though, as introductory materials often seem more like a barrier than an invitation to the study of life. This text offers a concise and accessible introduction to molecular biology, requiring no previous background in science, aimed at students and professionals in fields ranging from engineering to journalism—anyone who wants to get a foothold in this rapidly expanding field. It will be particularly useful for computer scientists exploring computational biology. A reader who has mastered the information in The Processes of Life is ready to move on to more complex material in almost any area of contemporary biology. |
| computer science with specialization in bioinformatics: Advances in Case-Based Reasoning Klaus-Dieter Althoff, Ralph Bergmann, Mirjam Minor, Alexandre Hanft, 2008-08-29 This volume contains the papers presented at the 9th European Conference on Case-Based Reasoning (ECCBR 2008). Case-based reasoning (CBR) is an arti?cial intelligence approach whereby new problems are solved by remembering, adapting and reusing solutions to a previously solved, similar problem. The collection of previously solved problems andtheirassociatedsolutionsisstoredinthecasebase. Neworadaptedsolutions are learned and updated in the case base as needed. In remembrance of the First European Workshop on Case-Based Reasoning, which took place 15 years ago at the European Academy Otzenhausen, not far from Trier, this year’s conference was especially devoted to the past, present, and future of case-based reasoning. ECCBR and the International Conference on Case-Based Reasoning (IC- CBR) alternate every year. ECCBR 2008 followed a series of seven successful European workshops previously held in Otzenhausen, Germany (1993), Ch- tilly, France (1994), Lausanne, Switzerland (1996), Dublin, Ireland (1998), and Trento, Italy (2000), and three European conferences in Aberdeen, UK (2002), ̈ Madrid, Spain (2004), and Olu ̈deniz/Fethiye, Turkey (2006). The International Conferences on Case-Based Reasoning (ICCBR) were previously held in Ses- bra, Portugal (1995), Providence, Rhode Island, USA (1997), Seeon, Germany (1999), Vancouver, Canada (2001), Trondheim, Norway (2003), Chicago, USA (2005), and Belfast, Northern Ireland (2007). These meetings have a history of attracting ?rst-class European and international researchers and practiti- ers. The proceedings of the ECCBR and ICCBR conferences are published by Springer in their LNAI series. |
| computer science with specialization in bioinformatics: Bioinformation Bronwyn Parry, Beth Greenhough, 2017-11-10 From DNA sequences stored on computer databases to archived forensic samples and biomedical records, bioinformation comes in many forms. Its unique provenance – the fact that it is 'mined' from the very fabric of the human body – makes it a mercurial resource; one that no one seemingly owns, but in which many have deeply vested interests. Who has the right to exploit and benefit from bioinformation? The individual or community from whom it was derived? The scientists and technicians who make its extraction both possible and meaningful or the commercial and political interests which fund this work? Who is excluded or even at risk from its commercialisation? And what threats and opportunities might the generation of 'Big Bioinformational Data' raise? In this groundbreaking book, authors Bronwyn Parry and Beth Greenhough explore the complex economic, social and political questions arising from the creation and use of bioinformation. Drawing on a range of highly topical cases, including the commercialization of human sequence data; the forensic use of retained bioinformation; biobanking and genealogical research, they show how demand for this resource has grown significantly driving a burgeoning but often highly controversial global economy in bioinformation. But, they argue, change is afoot as new models emerge that challenge the ethos of privatisation by creating instead a dynamic open source 'bioinformational commons' available for all future generations. |
| computer science with specialization in bioinformatics: Deep Learning for Coders with fastai and PyTorch Jeremy Howard, Sylvain Gugger, 2020-06-29 Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala |
| computer science with specialization in bioinformatics: Computational Molecular Biology S. Istrail, P. Pevzner, R. Shamir, 2003-04-02 This volume contains papers demonstrating the variety and richness of computational problems motivated by molecular biology. The application areas within biology that give rise to the problems studied in these papers include solid molecular modeling, sequence comparison, phylogeny, evolution, mapping, DNA chips, protein folding and 2D gel technology. The mathematical techniques used are algorithmics, combinatorics, optimization, probability, graph theory, complexity and applied mathematics. This is the fourth volume in the Discrete Applied Mathematics series on computational molecular biology, which is devoted to combinatorial and algorithmic techniques in computational molecular biology. This series publishes novel research results on the mathematical and algorithmic foundations of the inherently discrete aspects of computational biology. Key features: . protein folding . phylogenetic inference . 2-dimensional gel analysis . graphical models for sequencing by hybridisation . dynamic visualization of molecular surfaces . problems and algorithms in sequence alignment This book is a reprint of Discrete Applied Mathematics Volume 127, Number 1. |
| computer science with specialization in bioinformatics: Basic Bioinformatics S. Ignacimuthu, 2005 This book is intended to give the basics of biological concepts, biological database and internet based bioinformatic tools. We are hopeful that this book will cater to the immediate needs of students, researchers, faculty members and pharmaceutical industries.--Pref. |
Computer - Wikipedia
A computer is a machine that can be programmed to automatically carry out sequences of arithmetic or logical operations (computation). Modern digital electronic computers can …
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Oct 9, 2024 · A computer is a programmable machine that responds to specific instructions and uses hardware and software to perform tasks. Different types of computers, including …
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Computer - Wikipedia
A computer is a machine that can be programmed to automatically carry out sequences of arithmetic or logical operations (computation). Modern digital electronic computers can …
Computer | Definition, History, Operating Systems, & Facts
A computer is a programmable device for processing, storing, and displaying information. Learn more in this article about modern digital electronic computers and their design, constituent …
What is a Computer?
Feb 6, 2025 · What is a Computer? A computer is a programmable device that stores, retrieves, and processes data. The term "computer" was originally given to humans (human computers) …
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Shop Micro Center for electronics, PCs, laptops, Apple products, and much more. Enjoy in-store pickup, top deals, and expert same-day tech support.
What is a Computer? - GeeksforGeeks
Apr 7, 2025 · A computer is an electronic device that processes, stores, and executes instructions to perform tasks. It includes key components such as the CPU (Central Processing Unit), RAM …
Computer Basics: What is a Computer? - GCFGlobal.org
What is a computer? A computer is an electronic device that manipulates information, or data. It has the ability to store, retrieve, and process data. You may already know that you can use a …
What is a Computer? (Definition & Meaning) - Webopedia
Oct 9, 2024 · A computer is a programmable machine that responds to specific instructions and uses hardware and software to perform tasks. Different types of computers, including …
Computer - Simple English Wikipedia, the free encyclopedia
A computer is a machine that uses electronics to input, process, store, and output data. Data is information such as numbers, words, and lists. Input of data means to read information from a …
Laptop & Desktop Computers - Staples
Buy the computer that fits your exact needs. Choose from laptops, desktops PCs, notebooks, and accessories. Invest in a quality computer for work or personal use.
What is Computer? Definition, Characteristics and Classification
Aug 7, 2024 · A computer is an electronic device wherein we need to input raw data to be processed with a set of programs to produce a desirable output. Computers have the ability to …
