Download or read book Uncertainty in Biology written by Liesbet Geris and published by Springer. This book was released on 2015-10-26 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational modeling allows to reduce, refine and replace animal experimentation as well as to translate findings obtained in these experiments to the human background. However these biomedical problems are inherently complex with a myriad of influencing factors, which strongly complicates the model building and validation process. This book wants to address four main issues related to the building and validation of computational models of biomedical processes: 1. Modeling establishment under uncertainty 2. Model selection and parameter fitting 3. Sensitivity analysis and model adaptation 4. Model predictions under uncertainty In each of the abovementioned areas, the book discusses a number of key-techniques by means of a general theoretical description followed by one or more practical examples. This book is intended for graduate students and researchers active in the field of computational modeling of biomedical processes who seek to acquaint themselves with the different ways in which to study the parameter space of their model as well as its overall behavior.
Download or read book Cell Biology by the Numbers written by Ron Milo and published by Garland Science. This book was released on 2015-12-07 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Top 25 CHOICE 2016 Title, and recipient of the CHOICE Outstanding Academic Title (OAT) Award. How much energy is released in ATP hydrolysis? How many mRNAs are in a cell? How genetically similar are two random people? What is faster, transcription or translation?Cell Biology by the Numbers explores these questions and dozens of others provid
Download or read book Uncertainty written by Kostas Kampourakis and published by Oxford University Press, USA. This book was released on 2020 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Anti-evolutionists, climate denialists, and anti-vaxxers, among others, question some of the best-established scientific findings by referring to the uncertainties in these areas of research. Uncertainty: How It Makes Science Advance shows that uncertainty is an inherent feature of science that makes it advance by motivating further research.
Download or read book Quantitative Biology written by Brian Munsky and published by MIT Press. This book was released on 2018-08-21 with total page 729 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the quantitative modeling of biological processes, presenting modeling approaches, methodology, practical algorithms, software tools, and examples of current research. The quantitative modeling of biological processes promises to expand biological research from a science of observation and discovery to one of rigorous prediction and quantitative analysis. The rapidly growing field of quantitative biology seeks to use biology's emerging technological and computational capabilities to model biological processes. This textbook offers an introduction to the theory, methods, and tools of quantitative biology. The book first introduces the foundations of biological modeling, focusing on some of the most widely used formalisms. It then presents essential methodology for model-guided analyses of biological data, covering such methods as network reconstruction, uncertainty quantification, and experimental design; practical algorithms and software packages for modeling biological systems; and specific examples of current quantitative biology research and related specialized methods. Most chapters offer problems, progressing from simple to complex, that test the reader's mastery of such key techniques as deterministic and stochastic simulations and data analysis. Many chapters include snippets of code that can be used to recreate analyses and generate figures related to the text. Examples are presented in the three popular computing languages: Matlab, R, and Python. A variety of online resources supplement the the text. The editors are long-time organizers of the Annual q-bio Summer School, which was founded in 2007. Through the school, the editors have helped to train more than 400 visiting students in Los Alamos, NM, Santa Fe, NM, San Diego, CA, Albuquerque, NM, and Fort Collins, CO. This book is inspired by the school's curricula, and most of the contributors have participated in the school as students, lecturers, or both. Contributors John H. Abel, Roberto Bertolusso, Daniela Besozzi, Michael L. Blinov, Clive G. Bowsher, Fiona A. Chandra, Paolo Cazzaniga, Bryan C. Daniels, Bernie J. Daigle, Jr., Maciej Dobrzynski, Jonathan P. Doye, Brian Drawert, Sean Fancer, Gareth W. Fearnley, Dirk Fey, Zachary Fox, Ramon Grima, Andreas Hellander, Stefan Hellander, David Hofmann, Damian Hernandez, William S. Hlavacek, Jianjun Huang, Tomasz Jetka, Dongya Jia, Mohit Kumar Jolly, Boris N. Kholodenko, Markek Kimmel, Michał Komorowski, Ganhui Lan, Heeseob Lee, Herbert Levine, Leslie M Loew, Jason G. Lomnitz, Ard A. Louis, Grant Lythe, Carmen Molina-París, Ion I. Moraru, Andrew Mugler, Brian Munsky, Joe Natale, Ilya Nemenman, Karol Nienałtowski, Marco S. Nobile, Maria Nowicka, Sarah Olson, Alan S. Perelson, Linda R. Petzold, Sreenivasan Ponnambalam, Arya Pourzanjani, Ruy M. Ribeiro, William Raymond, William Raymond, Herbert M. Sauro, Michael A. Savageau, Abhyudai Singh, James C. Schaff, Boris M. Slepchenko, Thomas R. Sokolowski, Petr Šulc, Andrea Tangherloni, Pieter Rein ten Wolde, Philipp Thomas, Karen Tkach Tuzman, Lev S. Tsimring, Dan Vasilescu, Margaritis Voliotis, Lisa Weber
Download or read book Uncertainty in Pharmacology written by Adam LaCaze and published by Springer Nature. This book was released on 2020-02-20 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume covers a wide range of topics concerning methodological, epistemological, and regulatory-ethical issues around pharmacology. The book focuses in particular on the diverse sources of uncertainty, the different kinds of uncertainty that there are, and the diverse ways in which these uncertainties are (or could be) addressed. Compared with the more basic sciences, such as chemistry or biology, pharmacology works across diverse observable levels of reality: although the first step in the causal chain leading to the therapeutic outcome takes place at the biochemical level, the end-effect is a clinically observable result—which is influenced not only by biological actions, but also psychological and social phenomena. Issues of causality and evidence must be treated with these specific aspects in mind. In covering these issues, the book opens up a common domain of investigation which intersects the deeply intertwined dimensions of pharmacological research, pharmaceutical regulation and the related economic environment. The book is a collective endeavour with in-depth contributions from experts in pharmacology, philosophy of medicine, statistics, scientific methodology, formal and social epistemology, working in constant dialogue across disciplinary boundaries.
Download or read book Mathematics of Evolution and Phylogeny written by Olivier Gascuel and published by OUP Oxford. This book was released on 2005-02-24 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book considers evolution at different scales: sequences, genes, gene families, organelles, genomes and species. The focus is on the mathematical and computational tools and concepts, which form an essential basis of evolutionary studies, indicate their limitations, and give them orientation. Recent years have witnessed rapid progress in the mathematics of evolution and phylogeny, with models and methods becoming more realistic, powerful, and complex. Aimed at graduates and researchers in phylogenetics, mathematicians, computer scientists and biologists, and including chapters by leading scientists: A. Bergeron, D. Bertrand, D. Bryant, R. Desper, O. Elemento, N. El-Mabrouk, N. Galtier, O. Gascuel, M. Hendy, S. Holmes, K. Huber, A. Meade, J. Mixtacki, B. Moret, E. Mossel, V. Moulton, M. Pagel, M.-A. Poursat, D. Sankoff, M. Steel, J. Stoye, J. Tang, L.-S. Wang, T. Warnow, Z. Yang, this book of contributed chapters explains the basis and covers the recent results in this highly topical area.
Download or read book Probabilistic Boolean Networks written by Ilya Shmulevich and published by SIAM. This book was released on 2010-01-21 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first comprehensive treatment of probabilistic Boolean networks, unifying different strands of current research and addressing emerging issues.
Download or read book Decisions Uncertainty and the Brain written by Paul W. Glimcher and published by MIT Press. This book was released on 2004-09-17 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this provocative book, Paul Glimcher argues that economic theory may provide an alternative to the classical Cartesian model of the brain and behavior. Glimcher argues that Cartesian dualism operates from the false premise that the reflex is able to describe behavior in the real world that animals inhabit. A mathematically rich cognitive theory, he claims, could solve the most difficult problems that any environment could present, eliminating the need for dualism by eliminating the need for a reflex theory. Such a mathematically rigorous description of the neural processes that connect sensation and action, he explains, will have its roots in microeconomic theory. Economic theory allows physiologists to define both the optimal course of action that an animal might select and a mathematical route by which that optimal solution can be derived. Glimcher outlines what an economics-based cognitive model might look like and how one would begin to test it empirically. Along the way, he presents a fascinating history of neuroscience. He also discusses related questions about determinism, free will, and the stochastic nature of complex behavior.
Download or read book Gene Drives on the Horizon written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2016-08-28 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research on gene drive systems is rapidly advancing. Many proposed applications of gene drive research aim to solve environmental and public health challenges, including the reduction of poverty and the burden of vector-borne diseases, such as malaria and dengue, which disproportionately impact low and middle income countries. However, due to their intrinsic qualities of rapid spread and irreversibility, gene drive systems raise many questions with respect to their safety relative to public and environmental health. Because gene drive systems are designed to alter the environments we share in ways that will be hard to anticipate and impossible to completely roll back, questions about the ethics surrounding use of this research are complex and will require very careful exploration. Gene Drives on the Horizon outlines the state of knowledge relative to the science, ethics, public engagement, and risk assessment as they pertain to research directions of gene drive systems and governance of the research process. This report offers principles for responsible practices of gene drive research and related applications for use by investigators, their institutions, the research funders, and regulators.
Download or read book Modeling and Inverse Problems in the Presence of Uncertainty written by H. T. Banks and published by CRC Press. This book was released on 2014-04-01 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling and Inverse Problems in the Presence of Uncertainty collects recent research—including the authors’ own substantial projects—on uncertainty propagation and quantification. It covers two sources of uncertainty: where uncertainty is present primarily due to measurement errors and where uncertainty is present due to the modeling formulation itself. After a useful review of relevant probability and statistical concepts, the book summarizes mathematical and statistical aspects of inverse problem methodology, including ordinary, weighted, and generalized least-squares formulations. It then discusses asymptotic theories, bootstrapping, and issues related to the evaluation of correctness of assumed form of statistical models. The authors go on to present methods for evaluating and comparing the validity of appropriateness of a collection of models for describing a given data set, including statistically based model selection and comparison techniques. They also explore recent results on the estimation of probability distributions when they are embedded in complex mathematical models and only aggregate (not individual) data are available. In addition, they briefly discuss the optimal design of experiments in support of inverse problems for given models. The book concludes with a focus on uncertainty in model formulation itself, covering the general relationship of differential equations driven by white noise and the ones driven by colored noise in terms of their resulting probability density functions. It also deals with questions related to the appropriateness of discrete versus continuum models in transitions from small to large numbers of individuals. With many examples throughout addressing problems in physics, biology, and other areas, this book is intended for applied mathematicians interested in deterministic and/or stochastic models and their interactions. It is also suitable for scientists in biology, medicine, engineering, and physics working on basic modeling and inverse problems, uncertainty in modeling, propagation of uncertainty, and statistical modeling.
Download or read book Understanding Uncertainty written by Dennis V. Lindley and published by John Wiley & Sons. This book was released on 2006-08-28 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: A lively and informal introduction to the role of uncertainty and probability in people's lives from an everyday perspective From television game shows and gambling techniques to weather forecasting and the financial markets, virtually every aspect of modern life involves situations in which the outcomes are uncertain and of varying qualities. But as noted statistician Dennis Lindley writes in this distinctive text, "We want you to face up to uncertainty, not hide it away under false concepts, but to understand it and, moreover, to use the recent discoveries so that you can act in the face of uncertainty more sensibly than would have been possible without the skill." Accessibly written at an elementary level, this outstanding text examines uncertainty in various everyday situations and introduces readers to three rules--craftily laid out in the book--that prove uncertainty can be handled with as much confidence as ordinary logic. Combining a concept of utility with probability, the book insightfully demonstrates how uncertainty can be measured and used in everyday life, especially in decision-making and science. With a focus on understanding and using probability calculations, Understanding Uncertainty demystifies probability and: * Explains in straightforward detail the logic of uncertainty, its truths, and its falsehoods * Explores what has been learned in the twentieth century about uncertainty * Provides a logical, sensible method for acting in the face of uncertainty * Presents vignettes of great discoveries made in the twentieth century * Shows readers how to discern if another person--whether a lawyer, politician, scientist, or journalist--is talking sense, posing the right questions, or obtaining sound answers Requiring only a basic understanding of mathematical concepts and operations, Understanding Uncertainty is useful as a text for all students who have probability or statistics as part of their course, even at the most introductory level.
Download or read book Global Sensitivity Analysis written by Andrea Saltelli and published by John Wiley & Sons. This book was released on 2008-02-28 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex mathematical and computational models are used in all areas of society and technology and yet model based science is increasingly contested or refuted, especially when models are applied to controversial themes in domains such as health, the environment or the economy. More stringent standards of proofs are demanded from model-based numbers, especially when these numbers represent potential financial losses, threats to human health or the state of the environment. Quantitative sensitivity analysis is generally agreed to be one such standard. Mathematical models are good at mapping assumptions into inferences. A modeller makes assumptions about laws pertaining to the system, about its status and a plethora of other, often arcane, system variables and internal model settings. To what extent can we rely on the model-based inference when most of these assumptions are fraught with uncertainties? Global Sensitivity Analysis offers an accessible treatment of such problems via quantitative sensitivity analysis, beginning with the first principles and guiding the reader through the full range of recommended practices with a rich set of solved exercises. The text explains the motivation for sensitivity analysis, reviews the required statistical concepts, and provides a guide to potential applications. The book: Provides a self-contained treatment of the subject, allowing readers to learn and practice global sensitivity analysis without further materials. Presents ways to frame the analysis, interpret its results, and avoid potential pitfalls. Features numerous exercises and solved problems to help illustrate the applications. Is authored by leading sensitivity analysis practitioners, combining a range of disciplinary backgrounds. Postgraduate students and practitioners in a wide range of subjects, including statistics, mathematics, engineering, physics, chemistry, environmental sciences, biology, toxicology, actuarial sciences, and econometrics will find much of use here. This book will prove equally valuable to engineers working on risk analysis and to financial analysts concerned with pricing and hedging.
Download or read book Computational Methods in Systems Biology written by Olivier Roux and published by Springer. This book was released on 2015-09-01 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 13th International Conference on Computational Methods in Systems Biology, CMSB 2015, held in Nantes, France, in September 2015. The 20 full papers and 2 short papers presented were carefully reviewed and selected from 43 full and 4 short paper submissions. The papers cover a wide range of topics in the analysis of biological systems, networks and data such as model checking, stochastic analysis, hybrid systems, circadian clock, time series data, logic programming, and constraints solving ranging from intercellular to multiscale.
Download or read book Mathematics for Biological Scientists written by Mike Aitken and published by Garland Science. This book was released on 2009-09-30 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Algorithms in Structural Molecular Biology written by Bruce R. Donald and published by MIT Press. This book was released on 2023-08-15 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: An overview of algorithms important to computational structural biology that addresses such topics as NMR and design and analysis of proteins.Using the tools of information technology to understand the molecular machinery of the cell offers both challenges and opportunities to computational scientists. Over the past decade, novel algorithms have been developed both for analyzing biological data and for synthetic biology problems such as protein engineering. This book explains the algorithmic foundations and computational approaches underlying areas of structural biology including NMR (nuclear magnetic resonance); X-ray crystallography; and the design and analysis of proteins, peptides, and small molecules. Each chapter offers a concise overview of important concepts, focusing on a key topic in the field. Four chapters offer a short course in algorithmic and computational issues related to NMR structural biology, giving the reader a useful toolkit with which to approach the fascinating yet thorny computational problems in this area. A recurrent theme is understanding the interplay between biophysical experiments and computational algorithms. The text emphasizes the mathematical foundations of structural biology while maintaining a balance between algorithms and a nuanced understanding of experimental data. Three emerging areas, particularly fertile ground for research students, are highlighted: NMR methodology, design of proteins and other molecules, and the modeling of protein flexibility. The next generation of computational structural biologists will need training in geometric algorithms, provably good approximation algorithms, scientific computation, and an array of techniques for handling noise and uncertainty in combinatorial geometry and computational biophysics. This book is an essential guide for young scientists on their way to research success in this exciting field.
Download or read book Marine Conservation Biology written by Elliott A. Norse and published by . This book was released on 2005-05-09 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'Marine Conservation Biology' brings together leading experts from around the world to apply the lessons and thinking of conservation biology to marine issues. The contributors cover what is threatening marine biodiversity and what humans can do to recover the biological integrity of the world's oceans.
Download or read book Quantum Adaptivity in Biology From Genetics to Cognition written by Masanari Asano and published by Springer. This book was released on 2015-04-14 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
