Stochastic Models In The Life Sciences And Their Methods Of Analysis

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Stochastic Models In The Life Sciences And Their Methods Of Analysis

Wan Frederic Y M

Author : Wan Frederic Y M
Publisher : World Scientific
Page : 476 pages
File Size : 51,6 Mb
Release : 2019-08-29
Category : Mathematics
ISBN : 9789813274624

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Stochastic Models In The Life Sciences And Their Methods Of Analysis by Wan Frederic Y M Pdf

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 pre-requisites 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.

Stochastic Models in Biology

Narendra S. Goel,Nira Richter-Dyn

Author : Narendra S. Goel,Nira Richter-Dyn
Publisher : Elsevier
Page : 282 pages
File Size : 49,5 Mb
Release : 2016-01-26
Category : Science
ISBN : 9781483278100

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Stochastic Models in Biology by Narendra S. Goel,Nira Richter-Dyn Pdf

Stochastic Models in Biology describes the usefulness of the theory of stochastic process in studying biological phenomena. The book describes analysis of biological systems and experiments though probabilistic models rather than deterministic methods. The text reviews the mathematical analyses for modeling different biological systems such as the random processes continuous in time and discrete in state space. The book also discusses population growth and extinction through Malthus' law and the work of MacArthur and Wilson. The text then explains the dynamics of a population of interacting species. The book also addresses population genetics under systematic evolutionary pressures known as deterministic equations and genetic changes in a finite population known as stochastic equations. The text then turns to stochastic modeling of biological systems at the molecular level, particularly the kinetics of biochemical reactions. The book also presents various useful equations such as the differential equation for generating functions for birth and death processes. The text can prove valuable for biochemists, cellular biologists, and researchers in the medical and chemical field who are tasked to perform data analysis.

Stochastic Modelling of Social Processes

Andreas Diekmann,Peter Mitter

Author : Andreas Diekmann,Peter Mitter
Publisher : Academic Press
Page : 352 pages
File Size : 46,7 Mb
Release : 2014-05-10
Category : Social Science
ISBN : 9781483266565

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Stochastic Modelling of Social Processes by Andreas Diekmann,Peter Mitter Pdf

Stochastic Modelling of Social Processes provides information pertinent to the development in the field of stochastic modeling and its applications in the social sciences. This book demonstrates that stochastic models can fulfill the goals of explanation and prediction. Organized into nine chapters, this book begins with an overview of stochastic models that fulfill normative, predictive, and structural–analytic roles with the aid of the theory of probability. This text then examines the study of labor market structures using analysis of job and career mobility, which is one of the approaches taken by sociologists in research on the labor market. Other chapters consider the characteristic trends and patterns from data on divorces. This book discusses as well the two approaches of stochastic modeling of social processes, namely competing risk models and semi-Markov processes. The final chapter deals with the practical application of regression models of survival data. This book is a valuable resource for social scientists and statisticians.

Stochastic processes and applications in biology and medicine II

Marius Iosifescu,P. Tautu

Author : Marius Iosifescu,P. Tautu
Publisher : Springer
Page : 0 pages
File Size : 50,7 Mb
Release : 1973-07-25
Category : Mathematics
ISBN : 3540062718

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Stochastic processes and applications in biology and medicine II by Marius Iosifescu,P. Tautu Pdf

This volume is a revised and enlarged version of Chapter 3 of. a book with the same title, published in Romanian in 1968. The revision resulted in a new book which has been divided into two of the large amount of new material. The whole book parts because is intended to introduce mathematicians and biologists with a strong mathematical background to the study of stochastic processes and their applications in biological sciences. It is meant to serve both as a textbook and a survey of recent developments. Biology studies complex situations and therefore needs skilful methods of abstraction. Stochastic models, being both vigorous in their specification and flexible in their manipulation, are the most suitable tools for studying such situations. This circumstance deter mined the writing of this volume which represents a comprehensive cross section of modern biological problems on the theory of stochastic processes. Because of the way some specific problems have been treat ed, this volume may also be useful to research scientists in any other field of science, interested in the possibilities and results of stochastic modelling. To understand the material presented, the reader needs to be acquainted with probability theory, as given in a sound introductory course, and be capable of abstraction.

Methods and Models in Mathematical Biology

Johannes Müller,Christina Kuttler

Author : Johannes Müller,Christina Kuttler
Publisher : Springer
Page : 711 pages
File Size : 42,6 Mb
Release : 2015-08-13
Category : Mathematics
ISBN : 9783642272516

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Methods and Models in Mathematical Biology by Johannes Müller,Christina Kuttler Pdf

This book developed from classes in mathematical biology taught by the authors over several years at the Technische Universität München. The main themes are modeling principles, mathematical principles for the analysis of these models and model-based analysis of data. The key topics of modern biomathematics are covered: ecology, epidemiology, biochemistry, regulatory networks, neuronal networks and population genetics. A variety of mathematical methods are introduced, ranging from ordinary and partial differential equations to stochastic graph theory and branching processes. A special emphasis is placed on the interplay between stochastic and deterministic models.

Stochastic Modeling in Physical and Biological Sciences

V. Thangaraj,Gautam Choudhury

Author : V. Thangaraj,Gautam Choudhury
Publisher : Unknown
Page : 256 pages
File Size : 47,5 Mb
Release : 2016-06-28
Category : Stochastic processes
ISBN : 8184875444

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Stochastic Modeling in Physical and Biological Sciences by V. Thangaraj,Gautam Choudhury Pdf

Discusses basic definitions, important properties and results on Markov Chains giving examples to understand the intricacies of the theory of Markov Chains. This book elaborates continuous time stochastic processes for modeling purpose explaining in detail with examples and includes an application oriented chapter on how stochastic modeling throws light on physical sciences. Basics on branching processes and their applications are explained pedagogically with a view to develop modeling capacity in biological sciences. Queues are a ubiquitous part of everyday life. This volume throws light on the foundation for stochastic modeling on queues. Interestingly, it presents bulk service queues an offshoot of professor Medhi's foundation on queues. A monumental and seminal contribution of Professor Neuts on matrix geometric methods is presented in a neat form. Finally, it meticulously designs some stochastic biological models and shows how stochastic modeling can project the prosperity of biological sciences.

Stochastic Processes and Applications in Biology and Medicine

Marius Iosifescu,Petre Tăutu

Author : Marius Iosifescu,Petre Tăutu
Publisher : Unknown
Page : 348 pages
File Size : 55,8 Mb
Release : 1973
Category : Mathematics
ISBN : UCSD:31822000612895

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Stochastic Processes and Applications in Biology and Medicine by Marius Iosifescu,Petre Tăutu Pdf

Vol. 2.

An Introduction to Stochastic Modeling

Howard M. Taylor,Samuel Karlin

Author : Howard M. Taylor,Samuel Karlin
Publisher : Academic Press
Page : 410 pages
File Size : 50,6 Mb
Release : 2014-05-10
Category : Mathematics
ISBN : 9781483269276

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An Introduction to Stochastic Modeling by Howard M. Taylor,Samuel Karlin Pdf

An Introduction to Stochastic Modeling provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich diversity of applications of stochastic processes in the sciences. Organized into nine chapters, this book begins with an overview of diverse types of stochastic models, which predicts a set of possible outcomes weighed by their likelihoods or probabilities. This text then provides exercises in the applications of simple stochastic analysis to appropriate problems. Other chapters consider the study of general functions of independent, identically distributed, nonnegative random variables representing the successive intervals between renewals. This book discusses as well the numerous examples of Markov branching processes that arise naturally in various scientific disciplines. The final chapter deals with queueing models, which aid the design process by predicting system performance. This book is a valuable resource for students of engineering and management science. Engineers will also find this book useful.

Mathematics and Life Sciences

Alexandra V. Antoniouk,Roderick V. N. Melnik

Author : Alexandra V. Antoniouk,Roderick V. N. Melnik
Publisher : Walter de Gruyter
Page : 328 pages
File Size : 52,8 Mb
Release : 2012-12-19
Category : Mathematics
ISBN : 9783110288537

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Mathematics and Life Sciences by Alexandra V. Antoniouk,Roderick V. N. Melnik Pdf

The book provides a unique collection of in-depth mathematical, statistical, and modeling methods and techniques for life sciences, as well as their applications in a number of areas within life sciences. The book provides also with 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. Many areas within life sciences are becoming increasingly quantitative and the progress in those areas will be more and more dependent on the successful development of advanced mathematical, statistical and modelling methodologies and techniques. The state-of-the-art developments in such methodologies and techniques are scattered throughout research journals and hardly accessible to the practitioners in those areas. This book identifies a number of frontier areas where such methodologies and techniques have recently been developed and are to be published here for the first time, bringing substantial potential benefit to a range of applications in life sciences. In addition, the book contains several state-of-the-art surveys at the interface of mathematics and life sciences that would benefit a larger interdisciplinary community. It 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.

Stochastic Biomathematical Models

Mostafa Bachar,Jerry J. Batzel,Susanne Ditlevsen

Author : Mostafa Bachar,Jerry J. Batzel,Susanne Ditlevsen
Publisher : Springer
Page : 206 pages
File Size : 42,5 Mb
Release : 2012-10-19
Category : Mathematics
ISBN : 9783642321573

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Stochastic Biomathematical Models by Mostafa Bachar,Jerry J. Batzel,Susanne Ditlevsen Pdf

Stochastic biomathematical models are becoming increasingly important as new light is shed on the role of noise in living systems. In certain biological systems, stochastic effects may even enhance a signal, thus providing a biological motivation for the noise observed in living systems. Recent advances in stochastic analysis and increasing computing power facilitate the analysis of more biophysically realistic models, and this book provides researchers in computational neuroscience and stochastic systems with an overview of recent developments. Key concepts are developed in chapters written by experts in their respective fields. Topics include: one-dimensional homogeneous diffusions and their boundary behavior, large deviation theory and its application in stochastic neurobiological models, a review of mathematical methods for stochastic neuronal integrate-and-fire models, stochastic partial differential equation models in neurobiology, and stochastic modeling of spreading cortical depression.

Interacting Stochastic Systems

Jean-Dominique Deuschel

Author : Jean-Dominique Deuschel
Publisher : Springer Science & Business Media
Page : 470 pages
File Size : 40,9 Mb
Release : 2005-01-12
Category : Computers
ISBN : 3540230335

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Interacting Stochastic Systems by Jean-Dominique Deuschel Pdf

The Research Network on "Interacting stochastic systems of high complexity" set up by the German Research Foundation aimed at exploring and developing connections between research in infinite-dimensional stochastic analysis, statistical physics, spatial population models from mathematical biology, complex models of financial markets or of stochastic models interacting with other sciences. This book presents a structured collection of papers on the core topics, written at the close of the 6-year programme by the research groups who took part in it. The structure chosen highlights the interweaving of certain themes and certain interconnections discovered through the joint work. This yields a reference work on results and methods that will be useful to all who work between applied probability and the physical, economic, and life sciences.

Stochastic Epidemic Models and Their Statistical Analysis

Hakan Andersson,Tom Britton

Author : Hakan Andersson,Tom Britton
Publisher : Springer Science & Business Media
Page : 140 pages
File Size : 42,6 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461211587

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Stochastic Epidemic Models and Their Statistical Analysis by Hakan Andersson,Tom Britton Pdf

The present lecture notes describe stochastic epidemic models and methods for their statistical analysis. Our aim is to present ideas for such models, and methods for their analysis; along the way we make practical use of several probabilistic and statistical techniques. This will be done without focusing on any specific disease, and instead rigorously analyzing rather simple models. The reader of these lecture notes could thus have a two-fold purpose in mind: to learn about epidemic models and their statistical analysis, and/or to learn and apply techniques in probability and statistics. The lecture notes require an early graduate level knowledge of probability and They introduce several techniques which might be new to students, but our statistics. intention is to present these keeping the technical level at a minlmum. Techniques that are explained and applied in the lecture notes are, for example: coupling, diffusion approximation, random graphs, likelihood theory for counting processes, martingales, the EM-algorithm and MCMC methods. The aim is to introduce and apply these techniques, thus hopefully motivating their further theoretical treatment. A few sections, mainly in Chapter 5, assume some knowledge of weak convergence; we hope that readers not familiar with this theory can understand the these parts at a heuristic level. The text is divided into two distinct but related parts: modelling and estimation.

Issues in Biological and Life Sciences Research: 2011 Edition

Anonim

Author : Anonim
Publisher : ScholarlyEditions
Page : 5108 pages
File Size : 40,6 Mb
Release : 2012-01-09
Category : Science
ISBN : 9781464963339

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Issues in Biological and Life Sciences Research: 2011 Edition by Anonim Pdf

Issues in Biological and Life Sciences Research: 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Biological and Life Sciences Research. The editors have built Issues in Biological and Life Sciences Research: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Biological and Life Sciences Research in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Biological and Life Sciences Research: 2011 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

Stochastic Modelling for Systems Biology, Third Edition

Darren J. Wilkinson

Author : Darren J. Wilkinson
Publisher : CRC Press
Page : 292 pages
File Size : 46,5 Mb
Release : 2018-12-07
Category : Mathematics
ISBN : 9781351000895

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Stochastic Modelling for Systems Biology, Third Edition by Darren J. Wilkinson Pdf

Since the first edition of Stochastic Modelling for Systems Biology, there have been many interesting developments in the use of "likelihood-free" methods of Bayesian inference for complex stochastic models. Having been thoroughly updated to reflect this, this third edition covers everything necessary for a good appreciation of stochastic kinetic modelling of biological networks in the systems biology context. New methods and applications are included in the book, and the use of R for practical illustration of the algorithms has been greatly extended. There is a brand new chapter on spatially extended systems, and the statistical inference chapter has also been extended with new methods, including approximate Bayesian computation (ABC). Stochastic Modelling for Systems Biology, Third Edition is now supplemented by an additional software library, written in Scala, described in a new appendix to the book. New in the Third Edition New chapter on spatially extended systems, covering the spatial Gillespie algorithm for reaction diffusion master equation models in 1- and 2-d, along with fast approximations based on the spatial chemical Langevin equation Significantly expanded chapter on inference for stochastic kinetic models from data, covering ABC, including ABC-SMC Updated R package, including code relating to all of the new material New R package for parsing SBML models into simulatable stochastic Petri net models New open-source software library, written in Scala, replicating most of the functionality of the R packages in a fast, compiled, strongly typed, functional language Keeping with the spirit of earlier editions, all of the new theory is presented in a very informal and intuitive manner, keeping the text as accessible as possible to the widest possible readership. An effective introduction to the area of stochastic modelling in computational systems biology, this new edition adds additional detail and computational methods that will provide a stronger foundation for the development of more advanced courses in stochastic biological modelling.

Deterministic Versus Stochastic Modelling in Biochemistry and Systems Biology

Paola Lecca,Ian Laurenzi,Ferenc Jordan

Author : Paola Lecca,Ian Laurenzi,Ferenc Jordan
Publisher : Elsevier
Page : 411 pages
File Size : 43,8 Mb
Release : 2013-04-09
Category : Mathematics
ISBN : 9781908818218

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Deterministic Versus Stochastic Modelling in Biochemistry and Systems Biology by Paola Lecca,Ian Laurenzi,Ferenc Jordan Pdf

Stochastic kinetic methods are currently considered to be the most realistic and elegant means of representing and simulating the dynamics of biochemical and biological networks. Deterministic versus stochastic modelling in biochemistry and systems biology introduces and critically reviews the deterministic and stochastic foundations of biochemical kinetics, covering applied stochastic process theory for application in the field of modelling and simulation of biological processes at the molecular scale. Following an overview of deterministic chemical kinetics and the stochastic approach to biochemical kinetics, the book goes onto discuss the specifics of stochastic simulation algorithms, modelling in systems biology and the structure of biochemical models. Later chapters cover reaction-diffusion systems, and provide an analysis of the Kinfer and BlenX software systems. The final chapter looks at simulation of ecodynamics and food web dynamics. Introduces mathematical concepts and formalisms of deterministic and stochastic modelling through clear and simple examples Presents recently developed discrete stochastic formalisms for modelling biological systems and processes Describes and applies stochastic simulation algorithms to implement a stochastic formulation of biochemical and biological kinetics

Stochastic Models In The Life Sciences And Their Methods Of Analysis

Stochastic Models In The Life Sciences And Their Methods Of Analysis by Wan Frederic Y M Pdf

Stochastic Models in Biology by Narendra S. Goel,Nira Richter-Dyn Pdf

Stochastic Modelling of Social Processes by Andreas Diekmann,Peter Mitter Pdf

Stochastic processes and applications in biology and medicine II by Marius Iosifescu,P. Tautu Pdf

Methods and Models in Mathematical Biology by Johannes Müller,Christina Kuttler Pdf

Stochastic Modeling in Physical and Biological Sciences by V. Thangaraj,Gautam Choudhury Pdf

Stochastic Processes and Applications in Biology and Medicine by Marius Iosifescu,Petre Tăutu Pdf

An Introduction to Stochastic Modeling by Howard M. Taylor,Samuel Karlin Pdf

Mathematics and Life Sciences by Alexandra V. Antoniouk,Roderick V. N. Melnik Pdf

Stochastic Biomathematical Models by Mostafa Bachar,Jerry J. Batzel,Susanne Ditlevsen Pdf

Interacting Stochastic Systems by Jean-Dominique Deuschel Pdf

Stochastic Epidemic Models and Their Statistical Analysis by Hakan Andersson,Tom Britton Pdf

Issues in Biological and Life Sciences Research: 2011 Edition by Anonim Pdf

Stochastic Modelling for Systems Biology, Third Edition by Darren J. Wilkinson Pdf

Deterministic Versus Stochastic Modelling in Biochemistry and Systems Biology by Paola Lecca,Ian Laurenzi,Ferenc Jordan Pdf

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