Introductory Mathematics For The Life Sciences
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By David Phoenix Format : Pdf, ePub, Mobi, Kindle
 Publisher : CRC Press
 Isbn : 0203483030
 Pages : 229
 Category : Mathematics
 Reads : 369
 File Pdf: introductorymathematicsforthelifesciences.pdf
Book Summary:
Introductory Mathematics for the Life Sciences offers a straightforward introduction to the mathematical principles needed for studies in the life sciences. Starting with the basics of numbers, fractions, ratios, and percentages, the author explains progressively more sophisticated concepts, from algebra, measurement, and scientific notation through the linear, power, exponential, and logarithmic functions to introductory statistics. Worked examples illustrate concepts, applications, and interpretations, and exercises at the end of each chapter help readers apply and practice the skills they develop. Answers to the exercises are posted at the end of the text.
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By Yasuhiro Takeuchi,Yoh Iwasa,Kazunori Sato Format : Pdf, ePub, Mobi, Kindle
 Publisher : Springer Science & Business Media
 Isbn : 3540344268
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 File Pdf: mathematicsforlifescienceandmedicine.pdf
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The purpose of this volume is to present and discuss the many rich properties of the dynamical systems that appear in life science and medicine. It provides a fascinating survey of the theory of dynamical systems in biology and medicine. Each chapter will serve to introduce students and scholars to the stateoftheart in an exciting area, to present new results, and to inspire future contributions to mathematical modeling in life science and medicine.
Introductory Mathematics for the Life Sciences
By David Phoenix Format : Pdf, ePub, Mobi, Kindle
 Publisher : CRC Press
 Isbn : 1351989170
 Pages : 229
 Category : Mathematics
 Reads : 122
 File Pdf: introductorymathematicsforthelifesciences.pdf
Book Summary:
Introductory Mathematics for the Life Sciences offers a straightforward introduction to the mathematical principles needed for studies in the life sciences. Starting with the basics of numbers, fractions, ratios, and percentages, the author explains progressively more sophisticated concepts, from algebra, measurement, and scientific notation through the linear, power, exponential, and logarithmic functions to introductory statistics. Worked examples illustrate concepts, applications, and interpretations, and exercises at the end of each chapter help readers apply and practice the skills they develop. Answers to the exercises are posted at the end of the text.
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 File Pdf: anintroductiontodelaydifferentialequationswithapplicationstothelifesciences.pdf
Book Summary:
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Mathematics and the Natural Sciences
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 Publisher : Springer Science & Business Media
 Isbn : 1461472768
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 File Pdf: mathematicsforthelifesciences.pdf
Book Summary:
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 Publisher : Springer Science & Business Media
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 Pages : 646
 Category : Technology & Engineering
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 File Pdf: introductiontomathematicsforlifescientists.pdf
Book Summary:
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 File Pdf: essentialmathematicalbiology.pdf
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 File Pdf: themathematicsandmechanicsofbiologicalgrowth.pdf
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 File Pdf: mathematicalmodelsinbiology.pdf
Book Summary:
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 Publisher : Springer Science & Business Media
 Isbn : 354027877X
 Pages : 168
 Category : Mathematics
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 File Pdf: mathematicalmodelingforthelifesciences.pdf
Book Summary:
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 File Pdf: abiologistsguidetomathematicalmodelinginecologyandevolution.pdf
Book Summary:
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 File Pdf: mathematicalbiology.pdf
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 File Pdf: modelinglife.pdf
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This book develops the mathematical tools essential for students in the life sciences to describe interacting systems and predict their behavior. From predatorprey populations in an ecosystem, to hormone regulation within the body, the natural world abounds in dynamical systems that affect us profoundly. Complex feedback relations and counterintuitive responses are common in nature; this book develops the quantitative skills needed to explore these interactions. Differential equations are the natural mathematical tool for quantifying change, and are the driving force throughout this book. The use of Euler’s method makes nonlinear examples tractable and accessible to a broad spectrum of earlystage undergraduates, thus providing a practical alternative to the procedural approach of a traditional Calculus curriculum. Tools are developed within numerous, relevant examples, with an emphasis on the construction, evaluation, and interpretation of mathematical models throughout. Encountering these concepts in context, students learn not only quantitative techniques, but how to bridge between biological and mathematical ways of thinking. Examples range broadly, exploring the dynamics of neurons and the immune system, through to population dynamics and the Google PageRank algorithm. Each scenario relies only on an interest in the natural world; no biological expertise is assumed of student or instructor. Building on a single prerequisite of Precalculus, the book suits a twoquarter sequence for first or second year undergraduates, and meets the mathematical requirements of medical school entry. The later material provides opportunities for more advanced students in both mathematics and life sciences to revisit theoretical knowledge in a rich, realworld framework. In all cases, the focus is clear: how does the math help us understand the science?
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 Publisher : University of Chicago Press
 Isbn : 022637193X
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 File Pdf: quantifyinglife.pdf
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 File Pdf: introductiontobiologicalphysicsforthehealthandlifesciences.pdf
Book Summary:
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Book Summary:
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 Publisher : "O'Reilly Media, Inc."
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 File Pdf: deeplearningforcoderswithfastaiandpytorch.pdf
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Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this handson 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
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By Alexandra V. Antoniouk,Roderick V. N. Melnik Format : Pdf, ePub, Mobi, Kindle
 Publisher : Walter de Gruyter
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The book provides a unique collection of indepth mathematical, statistical, and modeling methods and techniques for life sciences, as well as their applications in a number of areas within life sciences. It also includes a range of new ideas that represent emerging frontiers in life sciences where the application of such quantitative methods and techniques is becoming increasingly important. The book is aimed at researchers in academia, practitioners and graduate students who want to foster interdisciplinary collaborations required to meet the challenges at the interface of modern life sciences and mathematics.
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By James D. Murray Format : Pdf, ePub, Mobi, Kindle
 Publisher : Springer Science & Business Media
 Isbn : 0387224378
 Pages : 551
 Category : Mathematics
 Reads : 345
 File Pdf: mathematicalbiology.pdf
Book Summary:
Mathematical Biology is a richly illustrated textbook in an exciting and fast growing field. Providing an indepth look at the practical use of math modeling, it features exercises throughout that are drawn from a variety of bioscientific disciplines  population biology, developmental biology, physiology, epidemiology, and evolution, among others. It maintains a consistent level throughout so that graduate students can use it to gain a foothold into this dynamic research area.
Mathematical Biology
By James D. Murray Format : Pdf, ePub, Mobi, Kindle
 Publisher : Springer Science & Business Media
 Isbn : 0387224378
 Pages : 551
 Category : Mathematics
 Reads : 874
 File Pdf: mathematicalbiology.pdf
Book Summary:
Mathematical Biology is a richly illustrated textbook in an exciting and fast growing field. Providing an indepth look at the practical use of math modeling, it features exercises throughout that are drawn from a variety of bioscientific disciplines  population biology, developmental biology, physiology, epidemiology, and evolution, among others. It maintains a consistent level throughout so that graduate students can use it to gain a foothold into this dynamic research area.
How Students Learn
By National Research Council,Division of Behavioral and Social Sciences and Education,Committee on How People Learn, A Targeted Report for Teachers Format : Pdf, ePub, Mobi, Kindle
 Publisher : National Academies Press
 Isbn : 0309133033
 Pages : 632
 Category : Education
 Reads : 717
 File Pdf: howstudentslearn.pdf
Book Summary:
How do you get a fourthgrader excited about history? How do you even begin to persuade high school students that mathematical functions are relevant to their everyday lives? In this volume, practical questions that confront every classroom teacher are addressed using the latest exciting research on cognition, teaching, and learning. How Students Learn: History, Mathematics, and Science in the Classroom builds on the discoveries detailed in the bestselling How People Learn. Now, these findings are presented in a way that teachers can use immediately, to revitalize their work in the classroom for even greater effectiveness. Organized for utility, the book explores how the principles of learning can be applied in teaching history, science, and math topics at three levels: elementary, middle, and high school. Leading educators explain in detail how they developed successful curricula and teaching approaches, presenting strategies that serve as models for curriculum development and classroom instruction. Their recounting of personal teaching experiences lends strength and warmth to this volume. The book explores the importance of balancing studentsâ€™ knowledge of historical fact against their understanding of concepts, such as change and cause, and their skills in assessing historical accounts. It discusses how to build straightforward science experiments into true understanding of scientific principles. And it shows how to overcome the difficulties in teaching math to generate real insight and reasoning in math students. It also features illustrated suggestions for classroom activities. How Students Learn offers a highly useful blend of principle and practice. It will be important not only to teachers, administrators, curriculum designers, and teacher educators, but also to parents and the larger community concerned about childrenâ€™s education.
Teaching and Learning of Calculus
By David Bressoud,Imène Ghedamsi,Victor MartinezLuaces,Günter Törner Format : Pdf, ePub, Mobi, Kindle
 Publisher : Springer
 Isbn : 3319329758
 Pages : 37
 Category : Education
 Reads : 856
 File Pdf: teachingandlearningofcalculus.pdf
Book Summary:
This survey focuses on the main trends in the field of calculus education. Despite their variety, the findings reveal a cornerstone issue that is strongly linked to the formalism of calculus concepts and to the difficulties it generates in the learning and teaching process. As a complement to the main text, an extended bibliography with some of the most important references on this topic is included. Since the diversity of the research in the field makes it difficult to produce an exhaustive stateoftheart summary, the authors discuss recent developments that go beyond this survey and put forward new research questions.
Stochastic Models In The Life Sciences And Their Methods Of Analysis
By Wan Frederic Y M Format : Pdf, ePub, Mobi, Kindle
 Publisher : World Scientific
 Isbn : 981327462X
 Pages : 476
 Category : Mathematics
 Reads : 852
 File Pdf: stochasticmodelsinthelifesciencesandtheirmethodsofanalysis.pdf
Book Summary:
Biological processes are evolutionary in nature and often evolve in a noisy environment or in the presence of uncertainty. Such evolving phenomena are necessarily modeled mathematically by stochastic differential/difference equations (SDE), which have been recognized as essential for a true understanding of many biological phenomena. Yet, there is a dearth of teaching material in this area for interested students and researchers, notwithstanding the addition of some recent texts on stochastic modelling in the life sciences. The reason may well be the demanding mathematical prerequisites needed to 'solve' SDE.A principal goal of this volume is to provide a working knowledge of SDE based on the premise that familiarity with the basic elements of a stochastic calculus for random processes is unavoidable. Through some SDE models of familiar biological phenomena, we show how stochastic methods developed for other areas of science and engineering are also useful in the life sciences. In the process, the volume introduces to biologists a collection of analytical and computational methods for research and applications in this emerging area of life science. The additions broaden the available tools for SDE models for biologists that have been limited by and large to stochastic simulations.
Statistics
By David W. Scott Format : Pdf, ePub, Mobi, Kindle
 Publisher : John Wiley & Sons
 Isbn : 1119675812
 Pages : 184
 Category : Mathematics
 Reads : 314
 File Pdf: statistics.pdf
Book Summary:
Statistic: A Concise Mathematical Introduction for Students and Scientists offers a one academic term text that prepares the student to broaden their skills in statistics, probability and inference, prior to selecting their followon courses in their chosen fields, whether it be engineering, computer science, programming, data sciences, business or economics. The book places focus early on continuous measurements, as well as discrete random variables. By invoking simple and intuitive models and geometric probability, discrete and continuous experiments and probabilities are discussed throughout the book in a natural way. Classical probability, random variables, and inference are discussed, as well as material on understanding data and topics of special interest. Topics discussed include: • Classical equally likely outcomes • Variety of models of discrete and continuous probability laws • Likelihood function and ratio • Inference • Bayesian statistics With the growth in the volume of data generated in many disciplines that is enabling the growth in data science, companies now demand statistically literate scientists and this textbook is the answer, suited for undergraduates studying science or engineering, be it computer science, economics, life sciences, environmental, business, amongst many others. Basic knowledge of bivariate calculus, R language, Matematica and JMP is useful, however there is an accompanying website including sample R and Mathematica code to help instructors and students.
Introduction to Modeling for Biosciences
By David J. Barnes,Dominique Chu Format : Pdf, ePub, Mobi, Kindle
 Publisher : Springer Science & Business Media
 Isbn : 1849963266
 Pages : 322
 Category : Computers
 Reads : 975
 File Pdf: introductiontomodelingforbiosciences.pdf
Book Summary:
Mathematical modeling can be a useful tool for researchers in the biological scientists. Yet in biological modeling there is no one modeling technique that is suitable for all problems. Instead, different problems call for different approaches. Furthermore, it can be helpful to analyze the same system using a variety of approaches, to be able to exploit the advantages and drawbacks of each. In practice, it is often unclear which modeling approaches will be most suitable for a particular biological question, a problem which requires researchers to know a reasonable amount about a number of techniques, rather than become experts on a single one. "Introduction to Modeling for Biosciences" addresses this issue by presenting a broad overview of the most important techniques used to model biological systems. In addition to providing an introduction into the use of a wide range of software tools and modeling environments, this helpful text/reference describes the constraints and difficulties that each modeling technique presents in practice, enabling the researcher to quickly determine which software package would be most useful for their particular problem. Topics and features: introduces a basic array of techniques to formulate models of biological systems, and to solve them; intersperses the text with exercises throughout the book; includes practical introductions to the Maxima computer algebra system, the PRISM model checker, and the Repast Simphony agent modeling environment; discusses agentbased models, stochastic modeling techniques, differential equations and Gillespie’s stochastic simulation algorithm; contains appendices on Repast batch running, rules of differentiation and integration, Maxima and PRISM notation, and some additional mathematical concepts; supplies source code for many of the example models discussed, at the associated website http://www.cs.kent.ac.uk/imb/. This unique and practical guide leads the novice modeler through realistic and concrete modeling projects, highlighting and commenting on the process of abstracting the real system into a model. Students and active researchers in the biosciences will also benefit from the discussions of the highquality, triedandtested modeling tools described in the book. Dr. David J. Barnes is a lecturer in computer science at the University of Kent, UK, with a strong background in the teaching of programming. Dr. Dominique Chu is a lecturer in computer science at the University of Kent, UK. He is an internationally recognized expert in agentbased modeling, and has also indepth research experience in stochastic and differential equation based modeling.
Introduction to MATLAB® for Biologists
By Cerian Ruth Webb,Mirela Domijan Format : Pdf, ePub, Mobi, Kindle
 Publisher : Springer
 Isbn : 3030213374
 Pages : 175
 Category : Science
 Reads : 285
 File Pdf: introductiontomatlabforbiologists.pdf
Book Summary:
This textbook takes you from the very first time you open MATLAB® through to a position where you can comfortably integrate this computer language into your research or studies. The book will familiarise you with the MATLAB interface, show you how to use the program ́s builtin functions and carefully guide you towards creating your own functions and scripts so that you can use MATLAB as a sophisticated tool to support your own research. A central aim of this book is to provide you with the core knowledge and skills required to become a confident MATLAB user so that you can find and make use of the many specialist functions and toolboxes that have been developed to support a wide range of biological applications. Examples presented within the book are selected to be relevant to biological scientists and they illustrate some of the many ways the program can be incorporated into, and used to enhance, your own research and studies. The textbook is a musthave for students and researchers in the biological sciences. It will also appeal to readers of all backgrounds who are looking for an introduction to MATLAB which is suitable for those with little or no experience of programming.
Applied Statistics with R
By Justin C. Touchon Format : Pdf, ePub, Mobi, Kindle
 Publisher : Oxford University Press
 Isbn : 0192640127
 Pages : 304
 Category : Science
 Reads : 932
 File Pdf: appliedstatisticswithr.pdf
Book Summary:
The statistical analyses that students of the lifesciences are being expected to perform are becoming increasingly advanced. Whether at the undergraduate, graduate, or postgraduate level, this book provides the tools needed to properly analyze your data in an efficient, accessible, plainspoken, frank, and occasionally humorous manner, ensuring that readers come away with the knowledge of which analyses they should use and when they should use them. The book uses the statistical language R, which is the choice of ecologists worldwide and is rapidly becoming the 'goto' stats program throughout the lifesciences. Furthermore, by using a single, realworld dataset throughout the book, readers are encouraged to become deeply familiar with an imperfect but realistic set of data. Indeed, early chapters are specifically designed to teach basic data manipulation skills and build good habits in preparation for learning more advanced analyses. This approach also demonstrates the importance of viewing data through different lenses, facilitating an easy and natural progression from linear and generalized linear models through to mixed effects versions of those same analyses. Readers will also learn advanced plotting and datawrangling techniques, and gain an introduction to writing their own functions. Applied Statistics with R is suitable for senior undergraduate and graduate students, professional researchers, and practitioners throughout the lifesciences, whether in the fields of ecology, evolution, environmental studies, or computational biology.
Introduction to Mathematical Biology
By Ching Shan Chou,Avner Friedman Format : Pdf, ePub, Mobi, Kindle
 Publisher : Springer
 Isbn : 3319296388
 Pages : 172
 Category : Mathematics
 Reads : 289
 File Pdf: introductiontomathematicalbiology.pdf
Book Summary:
This book is based on a one semester course that the authors have been teaching for several years, and includes two sets of case studies. The first includes chemostat models, predatorprey interaction, competition among species, the spread of infectious diseases, and oscillations arising from bifurcations. In developing these topics, readers will also be introduced to the basic theory of ordinary differential equations, and how to work with MATLAB without having any prior programming experience. The second set of case studies were adapted from recent and current research papers to the level of the students. Topics have been selected based on public health interest. This includes the risk of atherosclerosis associated with high cholesterol levels, cancer and immune interactions, cancer therapy, and tuberculosis. Readers will experience how mathematical models and their numerical simulations can provide explanations that guide biological and biomedical research. Considered to be the undergraduate companion to the more advanced book "Mathematical Modeling of Biological Processes" (A. Friedman, C.Y. Kao, Springer – 2014), this book is geared towards undergraduate students with little background in mathematics and no biological background.