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This book is designed specifically as a guide for Computer Scientists needing an introduction to Cell Biology. The text explores three different facets of biology: biological systems, experimental methods, and language and nomenclature. The author discusses what biologists are trying to determine from their experiments, how various experimental procedures are used and how they relate to accepted concepts in computer science, and the vocabulary necessary to read and understand current literature in biology. The book is an invaluable reference tool and an excellent starting point for a more comprehensive examination of cell biology.
Computing is revolutionizing the practice of biology. This book, which assumes no prior computing experience, provides students with the tools to write their own Python programs and to understand fundamental concepts in computational biology and bioinformatics. Each major part of the book begins with a compelling biological question, followed by the algorithmic ideas and programming tools necessary to explore it: the origins of pathogenicity are examined using gene finding, the evolutionary history of sex determination systems is studied using sequence alignment, and the origin of modern humans is addressed using phylogenetic methods. In addition to providing general programming skills, this book explores the design of efficient algorithms, simulation, NP-hardness, and the maximum likelihood method, among other key concepts and methods. Easy-to-read and designed to equip students with the skills to write programs for solving a range of biological problems, the book is accompanied by numerous programming exercises, available at www.cs.hmc.edu/CFB.
Computer graphics is being used to an increasing extent in the biological disciplines. As hardware costs drop and technological developments intro duce new graphics possibilities, researchers and teachers alike are becoming aware of the value of visual display methods. In this book we introduce the basics of computer graphics from the standpoints of both hardware and software, and review the main areas within biology to which computer graphics have been applied. The com puter graphics literature is vast, and we have not been able to give a full course on graphics techniques in these pages. We have instead tried to give a fairly balanced account of the use of graphics in biology, suitable for the reader with some elementary grounding in computer programming. We have included extensive references both to material cited in the text and to other relevant publications. One of the factors that has fuelled the increase in graphics use is the ease with which the more simple graphics techniques may be implemented on microcomputers. We hav.e, therefore, paid attention to microcomputer graphics as well as graphics techniques suitable for larger machines. Our examples range from simple two-dimensional graph plots to highly complex surface representations of molecules that require sophisticated graphics devices and mainframe computers on which to run. The book is separated into two logical sections. The first part con centrates on general graphics techniques, giving an overview from which the reader will be able to refer to other more specialised texts as required.
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.
Winner of the Computer History Museum Prize of the Special Interest Group: Computers, Information, and Society Imagine biology and medicine today without computers. What would laboratory work be like if electronic databases and statistical software did not exist? Would disciplines like genomics even be feasible if we lacked the means to manage and manipulate huge volumes of digital data? How would patients fare in a world absent CT scans, programmable pacemakers, and computerized medical records? Today, computers are a critical component of almost all research in biology and medicine. Yet, just fifty years ago, the study of life was by far the least digitized field of science, its living subject matter thought too complex and dynamic to be meaningfully analyzed by logic-driven computers. In this long-overdue study, historian Joseph November explores the early attempts, in the 1950s and 1960s, to computerize biomedical research in the United States. Computers and biomedical research are now so intimately connected that it is difficult to imagine when such critical work was offline. Biomedical Computing transports readers back to such a time and investigates how computers first appeared in the research lab and doctor's office. November examines the conditions that made possible the computerization of biology—including strong technological, institutional, and political support from the National Institutes of Health—and shows not only how digital technology transformed the life sciences but also how the intersection of the two led to important developments in computer architecture and software design. The history of this phenomenon has been only vaguely understood. November's thoroughly researched and lively study makes clear for readers the motives behind computerizing the study of life and how that technology profoundly affects biomedical research today.
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.
In the last years, it was observed an increasing interest of computer scientists in the structure of biological molecules and the way how they can be manipulated in vitro in order to define theoretical models of computation based on genetic engineering tools. Along the same lines, a parallel interest is growing regarding the process of evolution of living organisms. Much of the current data for genomes are expressed in the form of maps which are now becoming available and permit the study of the evolution of organisms at the scale of genome for the first time. On the other hand, there is an active trend nowadays throughout the field of computational biology toward abstracted, hierarchical views of biological sequences, which is very much in the spirit of computational linguistics. In the last decades, results and methods in the field of formal language theory that might be applied to the description of biological sequences were pointed out.
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Imagine a future world where computers can create universes -- digital environments made from binary ones and zeros. Imagine that within these universes there exist biological forms that reproduce, grow, and think. Imagine plantlike forms, ant colonies, immune systems, and brains, all adapting, evolving, and getting better at solving problems. Imagine if our computers became greenhouses for a new kind of nature. Just think what digital biology could do for us. Perhaps it could evolve new designs for us, think up ways to detect fraud using digital neurons, or solve scheduling problems with ants. Perhaps it could detect hackers with immune systems or create music from the patterns of growth of digital seashells. Perhaps it would allow our computers to become creative and inventive. Now stop imagining. digital biology is an intriguing glimpse into the future of technology by one of the most creative thinkers working in computer science today. As Peter J. Bentley explains, the next giant step in computing technology is already under way as computer scientists attempt to create digital universes that replicate the natural world. Within these digital universes, we will evolve solutions to problems, construct digital brains that can learn and think, and use immune systems to trap and destroy computer viruses. The biological world is the model for the next generation of computer software. By adapting the principles of biology, computer scientists will make it possible for computers to function as the natural world does. In practical terms, this will mean that we will soon have "smart" devices, such as houses that will keep the temperature as we like it and automobiles that will start only for drivers they recognize (through voice recognition or other systems) and that will navigate highways safely and with maximum fuel efficiency. Computers will soon be powerful enough and small enough that they can become part of clothing. "Digital agents" will be able to help us find a bank or restaurant in a city that we have never visited before, even as we walk through the airport. Miniature robots may even be incorporated into our bodies to monitor our health. Digital Biology is also an exploration of biology itself from a new perspective. We must understand how nature works in its most intimate detail before we can use these same biological processes inside our computers. Already scientists engaged in this work have gained new insights into the elegant simplicity of the natural universe. This is a visionary book, written in accessible, nontechnical language, that explains how cutting-edge computer science will shape our world in the coming decades.