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| define probability in biology: Chance in Biology Mark Denny, Steven Gaines, 2011-10-23 Life is a chancy proposition: from the movement of molecules to the age at which we die, chance plays a key role in the natural world. Traditionally, biologists have viewed the inevitable noise of life as an unfortunate complication. The authors of this book, however, treat random processes as a benefit. In this introduction to chance in biology, Mark Denny and Steven Gaines help readers to apply the probability theory needed to make sense of chance events--using examples from ocean waves to spiderwebs, in fields ranging from molecular mechanics to evolution. Through the application of probability theory, Denny and Gaines make predictions about how plants and animals work in a stochastic universe. Is it possible to pack a variety of ion channels into a cell membrane and have each operate at near-peak flow? Why are our arteries rubbery? The concept of a random walk provides the necessary insight. Is there an absolute upper limit to human life span? Could the sound of a cocktail party burst your eardrums? The statistics of extremes allows us to make the appropriate calculations. How long must you wait to see the detail in a moonlit landscape? Can you hear the noise of individual molecules? The authors provide answers to these and many other questions. After an introduction to the basic statistical methods to be used in this book, the authors emphasize the application of probability theory to biology rather than the details of the theory itself. Readers with an introductory background in calculus will be able to follow the reasoning, and sets of problems, together with their solutions, are offered to reinforce concepts. The use of real-world examples, numerous illustrations, and chapter summaries--all presented with clarity and wit--make for a highly accessible text. By relating the theory of probability to the understanding of form and function in living things, the authors seek to pique the reader's curiosity about statistics and provide a new perspective on the role of chance in biology. |
| define probability in biology: Probability and Mathematical Genetics N. H. Bingham, C. M. Goldie, 2010-07-15 No leading university department of mathematics or statistics, or library, can afford to be without this unique text. Leading authorities give a unique insight into a wide range of currently topical problems, from the mathematics of road networks to the genomics of cancer. |
| define probability in biology: What Is Life? A Guide to Biology W/Prep-U Jay Phelan, 2009-04-30 Jay Phelan's What is Life? A Guide to Biology is written in a delightfully readable style that communicates complex ideas to non-biology majors in a clear and approachable manner. After reading Phelan's book, students will understand why they would want to know and talk about science. His skillful style includes asking stimulating questions (called Q questions) which encourage the student to keep reading to find the answer and will illuminate just how relevant science is to their life. |
| define probability in biology: Philosophy Of Biology Elliott Sober, 2018-03-05 Perhaps because of it implications for our understanding of human nature, recent philosophy of biology has seen what might be the most dramatic work in the philosophies of the ?special? sciences. This drama has centered on evolutionary theory, and in the second edition of this textbook, Elliott Sober introduces the reader to the most important issues of these developments. With a rare combination of technical sophistication and clarity of expression, Sober engages both the higher level of theory and the direct implications for such controversial issues as creationism, teleology, nature versus nurture, and sociobiology. Above all, the reader will gain from this book a firm grasp of the structure of evolutionary theory, the evidence for it, and the scope of its explanatory significance. |
| define probability in biology: Principles of Biology Lisa Bartee, Walter Shiner, Catherine Creech, 2017 The Principles of Biology sequence (BI 211, 212 and 213) introduces biology as a scientific discipline for students planning to major in biology and other science disciplines. Laboratories and classroom activities introduce techniques used to study biological processes and provide opportunities for students to develop their ability to conduct research. |
| define probability in biology: Studies in the Philosophy of Biology Francisco Ayala, Francisco José Ayala, Francisco Jose Ayala, Theodosius Dobzhansky, 1974-01-01 |
| define probability in biology: Quantum Adaptivity in Biology: From Genetics to Cognition Masanari Asano, Andrei Khrennikov, Masanori Ohya, Yoshiharu Tanaka, Ichiro Yamato, 2015-04-14 This book examines information processing performed by bio-systems at all scales: from genomes, cells and proteins to cognitive and even social systems. It introduces a theoretical/conceptual principle based on quantum information and non-Kolmogorov probability theory to explain information processing phenomena in biology as a whole. The book begins with an introduction followed by two chapters devoted to fundamentals, one covering classical and quantum probability, which also contains a brief introduction to quantum formalism, and another on an information approach to molecular biology, genetics and epigenetics. It then goes on to examine adaptive dynamics, including applications to biology, and non-Kolmogorov probability theory. Next, the book discusses the possibility to apply the quantum formalism to model biological evolution, especially at the cellular level: genetic and epigenetic evolutions. It also presents a model of the epigenetic cellular evolution based on the mathematical formalism of open quantum systems. The last two chapters of the book explore foundational problems of quantum mechanics and demonstrate the power of usage of positive operator valued measures (POVMs) in biological science. This book will appeal to a diverse group of readers including experts in biology, cognitive science, decision making, sociology, psychology, and physics; mathematicians working on problems of quantum probability and information and researchers in quantum foundations. |
| define probability in biology: Mathematical Models in Biology Elizabeth Spencer Allman, John A. Rhodes, 2004 This introductory textbook on mathematical biology focuses on discrete models across a variety of biological subdisciplines. Biological topics treated include linear and non-linear models of populations, Markov models of molecular evolution, phylogenetic tree construction, genetics, and infectious disease models. The coverage of models of molecular evolution and phylogenetic tree construction from DNA sequence data is unique among books at this level. Computer investigations with MATLAB are incorporated throughout, in both exercises and more extensive projects, to give readers hands-on experience with the mathematical models developed. MATLAB programs accompany the text. Mathematical tools, such as matrix algebra, eigenvector analysis, and basic probability, are motivated by biological models and given self-contained developments, so that mathematical prerequisites are minimal. |
| define probability in biology: A Companion to the Philosophy of Biology Sahotra Sarkar, Anya Plutynski, 2010-11-08 A COMPANION TO THE PHILOSOPHY OF BIOLOGY “Sarkar is to be congratulated for assembling this talented team of philosophers, who are themselves to be congratulated for writing these interesting essays on so many fascinating areas in philosophy of biology. This book will be a wonderful resource for future work.” Elliot Sober, University of Wisconsin-Madison “Many of the discussions here start with a definition of terms and a historical context of the subject before delving into the deeper philosophical issues, making it a useful reference for students of biology as well as philosophy.” Northeastern Naturalist “The topics that are addressed are done so well. This book will appeal to the advanced student and knowledgeable amateur and may prove useful catalyst for discussion among research teams or those engaged in cross-disciplinary studies.” Reference Reviews A Companion to the Philosophy of Biology offers concise overviews of philosophical issues raised by all areas of biology. Addressing both traditional and emerging areas of philosophical interest, the volume focuses on the philosophical implications of evolutionary theory as well as key topics such as molecular biology, immunology, and ecology Comprising essays by top scholars in the field, this volume is an authoritative guide for professional philosophers, historians, sociologists and biologists, as well as an accessible reference work for students seeking to learn about this rapidly-changing field. |
| define probability in biology: Diffusion Processes and Related Topics in Biology Luigi M. Ricciardi, 2013-03-13 These notes are based on a one-quarter course given at the Department of Biophysics and Theoretical Biology of the University of Chicago in 1916. The course was directed to graduate students in the Division of Biological Sciences with interests in population biology and neurobiology. Only a slight acquaintance with probability and differential equations is required of the reader. Exercises are interwoven with the text to encourage the reader to play a more active role and thus facilitate his digestion of the material. One aim of these notes is to provide a heuristic approach, using as little mathematics as possible, to certain aspects of the theory of stochastic processes that are being increasingly employed in some of the population biol ogy and neurobiology literature. While the subject may be classical, the nov elty here lies in the approach and point of view, particularly in the applica tions such as the approach to the neuronal firing problem and its related dif fusion approximations. It is a pleasure to thank Professors Richard C. Lewontin and Arnold J.F. Siegert for their interest and support, and Mrs. Angell Pasley for her excellent and careful typing. I . PRELIMINARIES 1. Terminology and Examples Consider an experiment specified by: a) the experiment's outcomes, ~, forming the space S; b) certain subsets of S (called events) and by the probabilities of these events. |
| define probability in biology: Biology for Engineers, Second Edition Arthur T. Johnson, 2018-11-08 Biology is a critical application area for engineering analysis and design, and students in engineering programs as well as ecologists and environmentalists must be well-versed in the fundamentals of biology as they relate to their field. Biology for Engineers, Second Edition is an introductory text that minimizes unnecessary memorization of connections and classifications and instead emphasizes concepts, technology, and the utilization of living things. Whether students are headed toward a bio-related engineering degree or one of the more traditional majors, biology is so important that all engineering students should know how living things work and act. Emphasizing the ever-present interactions between a biological unit and its physical, chemical, and biological environments, the book provides ample instruction on the basics of physics, chemistry, mathematics, and engineering through a systems approach. It brings together all the concepts one needs to understand the role of biology in modern technology. Classroom-tested at the University of Maryland, this comprehensive text introduces concepts and terminology needed to understand more advanced biology literature. Filled with practical detailed examples, the book presents: Presents scientific principles relevant to biology that all engineers, ecologists and environmentalists must know A discussion of biological responses from the perspective of a broad range of fields such as psychology, human factors, genetics, plant and animal physiology, imaging, control systems, actuary, and medicine Includes end of chapter questions to test comprehension Provides updated material to reflect the latest research developments such as CRISPR. Introduces over 150 interesting application examples, incorporating a number of different engineering disciplines. Ties biological systems properties and behaviors to foundational sciences such as engineering sciences, chemistry, etc. |
| define probability in biology: Biology for AP ® Courses Julianne Zedalis, John Eggebrecht, 2017-10-16 Biology for AP® courses covers the scope and sequence requirements of a typical two-semester Advanced Placement® biology course. The text provides comprehensive coverage of foundational research and core biology concepts through an evolutionary lens. Biology for AP® Courses was designed to meet and exceed the requirements of the College Board’s AP® Biology framework while allowing significant flexibility for instructors. Each section of the book includes an introduction based on the AP® curriculum and includes rich features that engage students in scientific practice and AP® test preparation; it also highlights careers and research opportunities in biological sciences. |
| define probability in biology: Biology for Engineers Arthur T. Johnson, 2016-04-19 Biology is a critical application area for engineering analysis and design, and students in engineering programs must be well-versed in the fundamentals of biology as they relate to their field. Biology for Engineers is an introductory text that minimizes unnecessary memorization of connections and classifications and instead emphasizes concepts, technology, and the utilization of living things. Whether students are headed toward a bio-related engineering degree or one of the more traditional majors, biology is so important that all engineering students should know how living things work and act. Classroom-tested at the University of Maryland, this comprehensive text introduces concepts and terminology needed to understand more advanced biology literature. Filled with practical detailed examples, the book presents: Scientific principles relevant to biology that all engineers must know A discussion of biological responses from the perspective of a broad range of fields such as psychology, human factors, genetics, plant and animal physiology, imaging, control systems, actuary, and medicine A thorough examination of the scaling of biological responses and attributes A classification of different types of applications related to biological systems Tables of useful information that are nearly impossible to find elsewhere A series of questions at the end of each chapter to test comprehension Emphasizing the ever-present interactions between a biological unit and its physical, chemical, and biological environments, the book provides ample instruction on the basics of physics, chemistry, mathematics, and engineering. It brings together all of the concepts one needs to understand the role of biology in modern technology. |
| define probability in biology: Probability and Statistics Michael J. Evans, Jeffrey S. Rosenthal, 2004 Unlike traditional introductory math/stat textbooks, Probability and Statistics: The Science of Uncertainty brings a modern flavor based on incorporating the computer to the course and an integrated approach to inference. From the start the book integrates simulations into its theoretical coverage, and emphasizes the use of computer-powered computation throughout.* Math and science majors with just one year of calculus can use this text and experience a refreshing blend of applications and theory that goes beyond merely mastering the technicalities. They'll get a thorough grounding in probability theory, and go beyond that to the theory of statistical inference and its applications. An integrated approach to inference is presented that includes the frequency approach as well as Bayesian methodology. Bayesian inference is developed as a logical extension of likelihood methods. A separate chapter is devoted to the important topic of model checking and this is applied in the context of the standard applied statistical techniques. Examples of data analyses using real-world data are presented throughout the text. A final chapter introduces a number of the most important stochastic process models using elementary methods. *Note: An appendix in the book contains Minitab code for more involved computations. The code can be used by students as templates for their own calculations. If a software package like Minitab is used with the course then no programming is required by the students. |
| define probability in biology: Mathematics for Biological Scientists Mike Aitken, Bill Broadhurst, Stephen Hladky, 2009-09-30 Mathematics for Biological Scientists is a new undergraduate textbook which covers the mathematics necessary for biology students to understand, interpret and discuss biological questions. The book's twelve chapters are organized into four themes. The first theme covers the basic concepts of mathematics in biology, discussing the mathematics used in biological quantities, processes and structures. The second theme, calculus, extends the language of mathematics to describe change. The third theme is probability and statistics, where the uncertainty and variation encountered in real biological data is described. The fourth theme is explored briefly in the final chapter of the book, which is to show how the 'tools' developed in the first few chapters are used within biology to develop models of biological processes. Mathematics for Biological Scientists fully integrates mathematics and biology with the use of colour illustrations and photographs to provide an engaging and informative approach to the subject of mathematics and statistics within biological science. |
| define probability in biology: Mathematics, Developmental Biology and Tumour Growth Fernando Giráldez, Miguel Ángel Herrero, 2009 Developmental biology and tumour growth are two important areas of current research where mathematics increasingly provides powerful new techniques and insights. The unfolding complexity of living structures from egg to embryo gives rise to a number of difficult quantitative problems that are ripe for mathematical models and analysis. Understanding this early development process involves the study of pattern formation, which mathematicians view through the lens of dynamical systems. This book addresses several issues in developmental biology, including Notch signalling pathway integration and mesenchymal compartment formation. Tumour growth is one of the primary challenges of cancer research. Its study requires interdisciplinary approaches involving the close collaboration of mathematicians, biologists and physicians. The summer school addressed angiogenesis, modelling issues arising in radiotherapy, and tumour growth viewed from the individual cell and the relation to a multiphase-fluid flow picture of that process. This book is suitable for researchers, graduate students, and advanced undergraduates interested in mathematical methods of developmental biology or tumour growth. |
| define probability in biology: High-Dimensional Probability Roman Vershynin, 2018-09-27 An integrated package of powerful probabilistic tools and key applications in modern mathematical data science. |
| define probability in biology: The Book on Games of Chance Gerolamo Cardano, 2015-11-04 Mathematics was only one area of interest for Gerolamo Cardano ― the sixteenth-century astrologer, philosopher, and physician was also a prolific author and inveterate gambler. Gambling led Cardano to the study of probability, and he was the first writer to recognize that random events are governed by mathematical laws. Published posthumously in 1663, Cardano's Liber de ludo aleae (Book on Games of Chance) is often considered the major starting point of the study of mathematical probability. The Italian scholar formulated some of the field's basic ideas more than a century before the better-known correspondence of Pascal and Fermat. Although his book had no direct influence on other early thinkers about probability, it remains an important antecedent to later expressions of the science's tenets. |
| define probability in biology: Networks: From Biology to Theory Jianfeng Feng, Jürgen Jost, Minping Qian, 2007-09-04 Recent decades have witnessed the thriving development of new mathematical, computational and theoretical approaches, such as bioinformatics and neuroinformatics, to tackle fundamental issues in biology. These approaches focus no longer on individual units, such as nerve cells or genes, but rather on dynamic patterns of interactions between them. This volume explores the concept in full, featuring contributions from a global group of contributors, many of whom are pre-eminent in their field. |
| define probability in biology: Computational Methods in Systems Biology Pierpaolo Degano, Roberto Gorrieri, 2009-08-27 This volume contains the proceedings of the 7th Conference on Computational Methods in Systems Biology (CMSB 2009), held in Bologna, from August 31 to September 1, 2009. The ?rst CMSB was held in Trento in 2003, bringing together life scientists, computer scientists, engineers and physicists. The goal was to promote the c- vergence of di?erent disciplines aiming at a new understanding and description of biological systems, ?rmly ground in formal models, supported by compu- tionallanguagesandtools,ando?eringnew methodsofanalysis.The conference then moved to Paris in 2004, Edinburgh in 2005, Trento in 2006, Edinburgh in 2007 and Rostock/Warnemunde ̈ in 2008. This year the conference attracted about 45 submissions form 18 countries, mainly from Europe and North America, but also from Asia and Australia. We wish to thank all authors for their interest in CMSB 2009. After careful disc- sions, the Programme Committee eventually selected 18 papers for presentation at the conference. Each of them was accurately refereed by at least three - viewers, who delivered detailed and insightful comments and suggestions. The Conference Chairmen warmly thank all the members of the Programme C- mittee and all their sub-referees for the excellent support they gave, as well as for the friendly and constructive discussions. We also would like to thank the authorsfor havingrevisedtheir papers to addressthe comments andsuggestions by the referees. |
| define probability in biology: Plant Cell Biology William V Dashek, 2010-03-09 While there are a few plant cell biology books that are currently available, these are expensive, methods-oriented monographs. The present volume is a textbook for upper undergraduate and beginning graduate students. This textbook stresses concepts and is inquiry-oriented. To this end, there is extensive use of original research literature. As we live in an era of literature explosion, one must be selective. These judgements will naturally vary with each investigator. Input was sought from colleagues in deciding the literature to include. In addition to provision of select research literature, this volume presents citations and summaries of certain laboratory methods. In this connection, the textbook stresses quantitative data to enhance the student?s analytical abilities. Thus the volume contains computer-spread sheets and references to statistical packages, e.g. Harvard Graphics and Statistica. |
| define probability in biology: A Course in Mathematical Biology Gerda de Vries, Thomas Hillen, Mark Lewis, Johannes M?ller, Birgitt Sch?nfisch, 2006-07-01 This is the only book that teaches all aspects of modern mathematical modeling and that is specifically designed to introduce undergraduate students to problem solving in the context of biology. Included is an integrated package of theoretical modeling and analysis tools, computational modeling techniques, and parameter estimation and model validation methods, with a focus on integrating analytical and computational tools in the modeling of biological processes. Divided into three parts, it covers basic analytical modeling techniques; introduces computational tools used in the modeling of biological problems; and includes various problems from epidemiology, ecology, and physiology. All chapters include realistic biological examples, including many exercises related to biological questions. In addition, 25 open-ended research projects are provided, suitable for students. An accompanying Web site contains solutions and a tutorial for the implementation of the computational modeling techniques. Calculations can be done in modern computing languages such as Maple, Mathematica, and MATLAB?. |
| define probability in biology: Computational Molecular Biology Rajiv Tyagi, 2009 |
| define probability in biology: Biological Evolution and Statistical Physics M. Lässig, A. Valleriani, 2008-01-11 This set of lecture notes gives a first coherent account of a novel aspect of the living world that can be called biological information. The book presents both a pedagogical and state-of-the art roadmap of this rapidly evolving area and covers the whole field, from information which is encoded in the molecular genetic code to the description of large-scale evolution of complex species networks. The book will prove useful for all those who work at the interface of biology, physics and information science. |
| define probability in biology: Probability Models for DNA Sequence Evolution Rick Durrett, 2013-03-09 What underlying forces are responsible for the observed patterns of variability, given a collection of DNA sequences? In approaching this question a number of probability models are introduced and anyalyzed.Throughout the book, the theory is developed in close connection with data from more than 60 experimental studies that illustrate the use of these results. |
| define probability in biology: 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. |
| define probability in biology: CHSPE Preparation Book 2020-2021 Trivium High School Exam Prep Team, 2019-11-18 |
| define probability in biology: Physics Of Living Matter: Space, Time And Information, The - Proceedings Of The 27th Solvay Conference On Physics David J Gross, Alexander Sevrin, Boris Shraiman, 2020-03-06 This book is indexed in Chemical Abstracts ServiceEver since 1911, the Solvay Conferences have shaped modern physics. The format is quite different from other conferences as the emphasis is placed on discussion. The 27th edition held in October 2017 in Brussels and chaired by Boris Shraiman continued this tradition and addressed some of the most pressing open questions in the fields of biophysics, gathering many of the leading figures working on a wide variety of profound problems.The proceedings contain the 'rapporteur talks' giving a broad overview with unique insights by distinguished renowned scientists. These lectures cover the five sessions: 'Intra-cellular Structure and Dynamics', 'Cell Behavior and Control', 'Inter-cellular Interactions and Patterns', 'Morphogenesis', 'Evolutionary dynamics'.In the Solvay tradition, the proceedings also include the prepared comments to the rapporteur talks. The discussions among the participants — expert, yet lively and sometimes contentious — have been edited to retain their flavor and are reproduced in full. The reader is taken on a breathtaking ride through a fascinating field which is expanding rapidly and which was for the first time the subject of a Solvay Conference on Physics. |
| define probability in biology: Algorithms for Computational Biology Ian Holmes, Carlos Martín-Vide, Miguel A. Vega-Rodríguez, 2019-05-21 This book constitutes the proceedings of the 6th InternationalConference on Algorithms for Computational Biology, AlCoB 2019, held in Berkeley, CA, USA, in May 2019. The 15 full papers presented together with 1 invited paper were carefully reviewed and selected from 30 submissions. They are organized in the following topical sections: Biological networks and graph algorithms; genome rearrangement, assembly and classification; sequence analysis, phylogenetics and other biological processes. |
| define probability in biology: Mathematical Modelling & Computing in Biology and Medicine V. Capasso (Ed), 2003 |
| define probability in biology: Rules and Exceptions in Biology: from Fundamental Concepts to Applications Alfredo V. Peretti, |
| define probability in biology: Transactions on Computational Systems Biology XI Corrado Priami, 2009-09-07 This issue on Computational Models for Cell Processes is based on a workshop that took place in Turku, Finland, May 2008. The papers span a mix of approaches to systems biology, ranging from quantitative techniques to computing paradigms inspired by biology. |
| define probability in biology: Stochasticity in Processes Peter Schuster, 2016-10-14 This book has developed over the past fifteen years from a modern course on stochastic chemical kinetics for graduate students in physics, chemistry and biology. The first part presents a systematic collection of the mathematical background material needed to understand probability, statistics, and stochastic processes as a prerequisite for the increasingly challenging practical applications in chemistry and the life sciences examined in the second part. Recent advances in the development of new techniques and in the resolution of conventional experiments at nano-scales have been tremendous: today molecular spectroscopy can provide insights into processes down to scales at which current theories at the interface of physics, chemistry and the life sciences cannot be successful without a firm grasp of randomness and its sources. Routinely measured data is now sufficiently accurate to allow the direct recording of fluctuations. As a result, the sampling of data and the modeling of relevant processes are doomed to produce artifacts in interpretation unless the observer has a solid background in the mathematics of limited reproducibility. The material covered is presented in a modular approach, allowing more advanced sections to be skipped if the reader is primarily interested in applications. At the same time, most derivations of analytical solutions for the selected examples are provided in full length to guide more advanced readers in their attempts to derive solutions on their own. The book employs uniform notation throughout, and a glossary has been added to define the most important notions discussed. |
| define probability in biology: Foundations of Mathematical Biology Robert J. Rosen, 2013-10-22 Foundations of Mathematical Biology, Volume 1, Subcellular Systems, provides an introduction the place of mathematical biology in relation to the other biological, physical, and organizational sciences. It discusses the use of mathematical tools and techniques to solve biological problems. The book contains four chapters and begins with a discussion of the nature of hierarchical control in living matter. This is followed by a chapter on chemical kinetics and enzyme kinetics, covering the physicomathematical principles, models, and approximations underlying transition-state theory and the unimolecular reaction. Subsequent chapters deal with quantum genetics and membrane excitability. |
| define probability in biology: Encyclopedia of Evolutionary Biology , 2016-04-14 Encyclopedia of Evolutionary Biology, Four Volume Set is the definitive go-to reference in the field of evolutionary biology. It provides a fully comprehensive review of the field in an easy to search structure. Under the collective leadership of fifteen distinguished section editors, it is comprised of articles written by leading experts in the field, providing a full review of the current status of each topic. The articles are up-to-date and fully illustrated with in-text references that allow readers to easily access primary literature. While all entries are authoritative and valuable to those with advanced understanding of evolutionary biology, they are also intended to be accessible to both advanced undergraduate and graduate students. Broad topics include the history of evolutionary biology, population genetics, quantitative genetics; speciation, life history evolution, evolution of sex and mating systems, evolutionary biogeography, evolutionary developmental biology, molecular and genome evolution, coevolution, phylogenetic methods, microbial evolution, diversification of plants and fungi, diversification of animals, and applied evolution. Presents fully comprehensive content, allowing easy access to fundamental information and links to primary research Contains concise articles by leading experts in the field that ensures current coverage of each topic Provides ancillary learning tools like tables, illustrations, and multimedia features to assist with the comprehension process |
| define probability in biology: Principles of Computational Cell Biology Volkhard Helms, 2019-04-29 Computational cell biology courses are increasingly obligatory for biology students around the world but of course also a must for mathematics and informatics students specializing in bioinformatics. This book, now in its second edition is geared towards both audiences. The author, Volkhard Helms, has, in addition to extensive teaching experience, a strong background in biology and informatics and knows exactly what the key points are in making the book accessible for students while still conveying in depth knowledge of the subject.About 50% of new content has been added for the new edition. Much more room is now given to statistical methods, and several new chapters address protein-DNA interactions, epigenetic modifications, and microRNAs. |
| define probability in biology: 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 |
| define probability in biology: Progress in Theoretical Biology Robert J. Rosen, 2013-09-03 Progress in Theoretical Biology, Volume 6 covers the theoretical analysis of biological phenomena. The book discusses the potentials in chemical systems far from thermodynamic equilibrium, particularly the reduction of reaction-diffusion systems to catastrophe theory; and a form of logic suited for biology. The text describes the order-disorder transitions in polyelectrolytes and the chaos in systems in population biology. An artificial cognitive-plus-motivational system and pattern generation in networks are also encompassed. Biophysicists and physiologists will find the book invaluable. |
| define probability in biology: A Systems Theoretic Approach to Systems and Synthetic Biology I: Models and System Characterizations Vishwesh V. Kulkarni, Guy-Bart Stan, Karthik Raman, 2014-07-03 The complexity of biological systems has intrigued scientists from many disciplines and has given birth to the highly influential field of systems biology wherein a wide array of mathematical techniques, such as flux balance analysis, and technology platforms, such as next generation sequencing, is used to understand, elucidate, and predict the functions of complex biological systems. More recently, the field of synthetic biology, i.e., de novo engineering of biological systems, has emerged. Scientists from various fields are focusing on how to render this engineering process more predictable, reliable, scalable, affordable, and easy. Systems and control theory is a branch of engineering and applied sciences that rigorously deals with the complexities and uncertainties of interconnected systems with the objective of characterising fundamental systemic properties such as stability, robustness, communication capacity, and other performance metrics. Systems and control theory also strives to offer concepts and methods that facilitate the design of systems with rigorous guarantees on these properties. Over the last 100 years, it has made stellar theoretical and technological contributions in diverse fields such as aerospace, telecommunication, storage, automotive, power systems, and others. Can it have, or evolve to have, a similar impact in biology? The chapters in this book demonstrate that, indeed, systems and control theoretic concepts and techniques can have a significant impact in systems and synthetic biology. Volume I provides a panoramic view that illustrates the potential of such mathematical methods in systems and synthetic biology. Recent advances in systems and synthetic biology have clearly demonstrated the benefits of a rigorous and systematic approach rooted in the principles of systems and control theory - not only does it lead to exciting insights and discoveries but it also reduces the inordinately lengthy trial-and-error process of wet-lab experimentation, thereby facilitating significant savings in human and financial resources. In Volume I, some of the leading researchers in the field of systems and synthetic biology demonstrate how systems and control theoretic concepts and techniques can be useful, or should evolve to be useful, in order to understand how biological systems function. As the eminent computer scientist Donald Knuth put it, biology easily has 500 years of exciting problems to work on. This edited book presents but a small fraction of those for the benefit of (1) systems and control theorists interested in molecular and cellular biology and (2) biologists interested in rigorous modelling, analysis and control of biological systems. |
| define probability in biology: Introduction to Cell Mechanics and Mechanobiology Christopher R. Jacobs, Hayden Huang, Ronald Y. Kwon, 2012-11-16 Introduction to Cell Mechanics and Mechanobiology is designed for a one-semester course in the mechanics of the cell offered to advanced undergraduate and graduate students in biomedical engineering, bioengineering, and mechanical engineering. It teaches a quantitative understanding of the way cells detect, modify, and respond to the physical prope |
DEFINE Definition & Meaning - Merriam-Webster
The meaning of DEFINE is to determine or identify the essential qualities or meaning of. How to use define in a sentence.
DEFINE Definition & Meaning | Dictionary.com
Define definition: to state or set forth the meaning of (a word, phrase, etc.).. See examples of DEFINE used in a sentence.
DEFINE | English meaning - Cambridge Dictionary
DEFINE definition: 1. to say what the meaning of something, especially a word, is: 2. to explain and describe the…. Learn more.
DEFINE definition and meaning | Collins English Dictionary
If you define something, you show, describe, or state clearly what it is and what its limits are, or what it is like. We were unable to define what exactly was wrong with him. [ VERB wh ]
Define - definition of define by The Free Dictionary
define - show the form or outline of; "The tree was clearly defined by the light"; "The camera could define the smallest object"
DEFINE - Definition & Meaning - Reverso English Dictionary
Define definition: state the meaning of a word or phrase. Check meanings, examples, usage tips, pronunciation, domains, related words.
define - Wiktionary, the free dictionary
May 13, 2025 · define (third-person singular simple present defines, present participle defining, simple past and past participle defined) To determine with precision; to mark out with …
Define: Definition, Meaning, and Examples - usdictionary.com
Dec 24, 2024 · The word "define" means to explain or clarify the meaning of something or to establish boundaries and parameters. It is a versatile word used in many contexts, from …
Define Definition & Meaning - YourDictionary
Define Sentence Examples The child's eagerness and interest carry her over many obstacles that would be our undoing if we stopped to define and explain everything. It will not be welfare (or, …
DEFINITION Definition & Meaning - Merriam-Webster
The meaning of DEFINITION is a statement of the meaning of a word or word group or a sign or symbol. How to use definition in a sentence.
DEFINE Definition & Meaning - Merriam-Webster
The meaning of DEFINE is to determine or identify the essential qualities or meaning of. How to use define in a sentence.
DEFINE Definition & Meaning | Dictionary.com
Define definition: to state or set forth the meaning of (a word, phrase, etc.).. See examples of DEFINE used in a sentence.
DEFINE | English meaning - Cambridge Dictionary
DEFINE definition: 1. to say what the meaning of something, especially a word, is: 2. to explain and describe the…. Learn more.
DEFINE definition and meaning | Collins English Dictionary
If you define something, you show, describe, or state clearly what it is and what its limits are, or what it is like. We were unable to define what exactly was wrong with him. [ VERB wh ]
Define - definition of define by The Free Dictionary
define - show the form or outline of; "The tree was clearly defined by the light"; "The camera could define the smallest object"
DEFINE - Definition & Meaning - Reverso English Dictionary
Define definition: state the meaning of a word or phrase. Check meanings, examples, usage tips, pronunciation, domains, related words.
define - Wiktionary, the free dictionary
May 13, 2025 · define (third-person singular simple present defines, present participle defining, simple past and past participle defined) To determine with precision; to mark out with …
Define: Definition, Meaning, and Examples - usdictionary.com
Dec 24, 2024 · The word "define" means to explain or clarify the meaning of something or to establish boundaries and parameters. It is a versatile word used in many contexts, from …
Define Definition & Meaning - YourDictionary
Define Sentence Examples The child's eagerness and interest carry her over many obstacles that would be our undoing if we stopped to define and explain everything. It will not be welfare (or, …
DEFINITION Definition & Meaning - Merriam-Webster
The meaning of DEFINITION is a statement of the meaning of a word or word group or a sign or symbol. How to use definition in a sentence.
