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Biological Modeling and Simulation

Biological Modeling and Simulation Author Russell Schwartz
ISBN-10 9780262303392
Release 2008-07-25
Pages 408
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There are many excellent computational biology resources now available for learning about methods that have been developed to address specific biological systems, but comparatively little attention has been paid to training aspiring computational biologists to handle new and unanticipated problems. This text is intended to fill that gap by teaching students how to reason about developing formal mathematical models of biological systems that are amenable to computational analysis. It collects in one place a selection of broadly useful models, algorithms, and theoretical analysis tools normally found scattered among many other disciplines. It thereby gives the aspiring student a bag of tricks that will serve him or her well in modeling problems drawn from numerous subfields of biology. These techniques are taught from the perspective of what the practitioner needs to know to use them effectively, supplemented with references for further reading on more advanced use of each method covered. The text, which grew out of a class taught at Carnegie Mellon University, covers models for optimization, simulation and sampling, and parameter tuning. These topics provide a general framework for learning how to formulate mathematical models of biological systems, what techniques are available to work with these models, and how to fit the models to particular systems. Their application is illustrated by many examples drawn from a variety of biological disciplines and several extended case studies that show how the methods described have been applied to real problems in biology.



Algorithms in Structural Molecular Biology

Algorithms in Structural Molecular Biology Author Bruce R. Donald
ISBN-10 9780262297844
Release 2011-06-01
Pages 464
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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.



Mining the Biomedical Literature

Mining the Biomedical Literature Author Hagit Shatkay
ISBN-10 9780262304245
Release 2012-08-10
Pages 150
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The introduction of high-throughput methods has transformed biology into a data-rich science. Knowledge about biological entities and processes has traditionally been acquired by thousands of scientists through decades of experimentation and analysis. The current abundance of biomedical data is accompanied by the creation and quick dissemination of new information. Much of this information and knowledge, however, is represented only in text form--in the biomedical literature, lab notebooks, Web pages, and other sources. Researchers' need to find relevant information in the vast amounts of text has created a surge of interest in automated text-analysis.In this book, Hagit Shatkay and Mark Craven offer a concise and accessible introduction to key ideas in biomedical text mining. The chapters cover such topics as the relevant sources of biomedical text; text-analysis methods in natural language processing; the tasks of information extraction, information retrieval, and text categorization; and methods for empirically assessing text-mining systems. Finally, the authors describe several applications that recognize entities in text and link them to other entities and data resources, support the curation of structured databases, and make use of text to enable further prediction and discovery.



Kernel Methods in Computational Biology

Kernel Methods in Computational Biology Author Bernhard Schölkopf
ISBN-10 0262195097
Release 2004
Pages 400
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A detailed overview of current research in kernel methods and their application to computational biology.



Combinatorics of Genome Rearrangements

Combinatorics of Genome Rearrangements Author Guillaume Fertin
ISBN-10 9780262062824
Release 2009
Pages 288
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A comprehensive survey of a rapidly expanding field of combinatorial optimization,mathematically oriented but offering biological explanations when required.



Introduction to Computational Biology

Introduction to Computational Biology Author Bernhard Haubold
ISBN-10 9783764373870
Release 2006-08-09
Pages 328
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Written with the advanced undergraduate in mind, this book introduces into the field of Bioinformatics. The authors explain the computational and conceptional background to the analysis of large-scale sequence data. Many of the corresponding analysis methods are rooted in evolutionary thinking, which serves as a common thread throughout the book. The focus is on methods of comparative genomics and subjects covered include: alignments, gene finding, phylogeny, and the analysis of single nucleotide polymorphisms (SNPs). The volume contains exercises, questions & answers to selected problems.



Mathematical Modeling in Systems Biology

Mathematical Modeling in Systems Biology Author Brian P. Ingalls
ISBN-10 9780262315647
Release 2013-07-05
Pages 424
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Systems techniques are integral to current research in molecular cell biology, and system-level investigations are often accompanied by mathematical models. These models serve as working hypotheses: they help us to understand and predict the behavior of complex systems. This book offers an introduction to mathematical concepts and techniques needed for the construction and interpretation of models in molecular systems biology. It is accessible to upper-level undergraduate or graduate students in life science or engineering who have some familiarity with calculus, and will be a useful reference for researchers at all levels.The first four chapters cover the basics of mathematical modeling in molecular systems biology. The last four chapters address specific biological domains, treating modeling of metabolic networks, of signal transduction pathways, of gene regulatory networks, and of electrophysiology and neuronal action potentials. Chapters 3--8 end with optional sections that address more specialized modeling topics. Exercises, solvable with pen-and-paper calculations, appear throughout the text to encourage interaction with the mathematical techniques. More involved end-of-chapter problem sets require computational software. Appendixes provide a review of basic concepts of molecular biology, additional mathematical background material, and tutorials for two computational software packages (XPPAUT and MATLAB) that can be used for model simulation and analysis.



Numerical Methods and Advanced Simulation in Biomechanics and Biological Processes

Numerical Methods and Advanced Simulation in Biomechanics and Biological Processes Author Miguel Cerrolaza
ISBN-10 9780128117194
Release 2017-10-17
Pages 454
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Numerical Methods and Advanced Simulation in Biomechanics and Biological Processes covers new and exciting modeling methods to help bioengineers tackle problems for which the Finite Element Method is not appropriate. The book covers a wide range of important subjects in the field of numerical methods applied to biomechanics, including bone biomechanics, tissue and cell mechanics, 3D printing, computer assisted surgery and fluid dynamics. Modeling strategies, technology and approaches are continuously evolving as the knowledge of biological processes increases. Both theory and applications are covered, making this an ideal book for researchers, students and R&D professionals. Provides non-conventional analysis methods for modeling Covers the Discrete Element Method (DEM), Particle Methods (PM), MessLess and MeshFree Methods (MLMF), Agent-Based Methods (ABM), Lattice-Boltzmann Methods (LBM) and Boundary Integral Methods (BIM) Includes contributions from several world renowned experts in their fields Compares pros and cons of each method to help you decide which method is most applicable to solving specific problems



Statistical Modeling and Machine Learning for Molecular Biology

Statistical Modeling and Machine Learning for Molecular Biology Author Alan Moses
ISBN-10 9781482258608
Release 2017-01-06
Pages 280
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Molecular biologists are performing increasingly large and complicated experiments, but often have little background in data analysis. The book is devoted to teaching the statistical and computational techniques molecular biologists need to analyze their data. It explains the big-picture concepts in data analysis using a wide variety of real-world molecular biological examples such as eQTLs, ortholog identification, motif finding, inference of population structure, protein fold prediction and many more. The book takes a pragmatic approach, focusing on techniques that are based on elegant mathematics yet are the simplest to explain to scientists with little background in computers and statistics.



Learning and Inference in Computational Systems Biology

Learning and Inference in Computational Systems Biology Author Neil D. Lawrence
ISBN-10 STANFORD:36105215298956
Release 2010
Pages 362
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Tools and techniques for biological inference problems at scales ranging from genome-wide to pathway-specific.



Multiscale Modeling of Cancer

Multiscale Modeling of Cancer Author Vittorio Cristini
ISBN-10 9781139491501
Release 2010-09-09
Pages
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Mathematical modeling, analysis and simulation are set to play crucial roles in explaining tumor behavior, and the uncontrolled growth of cancer cells over multiple time and spatial scales. This book, the first to integrate state-of-the-art numerical techniques with experimental data, provides an in-depth assessment of tumor cell modeling at multiple scales. The first part of the text presents a detailed biological background with an examination of single-phase and multi-phase continuum tumor modeling, discrete cell modeling, and hybrid continuum-discrete modeling. In the final two chapters, the authors guide the reader through problem-based illustrations and case studies of brain and breast cancer, to demonstrate the future potential of modeling in cancer research. This book has wide interdisciplinary appeal and is a valuable resource for mathematical biologists, biomedical engineers and clinical cancer research communities wishing to understand this emerging field.



40 Days of Dating

40 Days of Dating Author Jessica Walsh
ISBN-10 9781613127155
Release 2015-01-20
Pages 304
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When New York–based graphic designers and long-time friends Timothy Goodman and Jessica Walsh found themselves single at the same time, they decided to try an experiment. The old adage says that it takes 40 days to change a habit—could the same be said for love? So they agreed to date each other for 40 days, record their experiences in questionnaires, photographs, videos, texts, and artworks, and post the material on a website they would create for this purpose. What began as a small experiment between two friends became an Internet sensation, drawing 5 million unique (and obsessed) visitors from around the globe to their site and their story since it was launched in July 2013. 40 Days of Dating: An Experiment is a beautifully designed, expanded look at the experiment and the results, including a great deal of material that never made it onto the site, such as who they were as friends and individuals before the 40 days and who they have become since. Note: 40 Days of Dating has a special binding that allows it to open very flat by attaching the endpapers to the inside covers.



Dynamic Systems Biology Modeling and Simulation

Dynamic Systems Biology Modeling and Simulation Author Joseph DiStefano III
ISBN-10 9780124104938
Release 2015-01-10
Pages 884
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Dynamic Systems Biology Modeling and Simuation consolidates and unifies classical and contemporary multiscale methodologies for mathematical modeling and computer simulation of dynamic biological systems – from molecular/cellular, organ-system, on up to population levels. The book pedagogy is developed as a well-annotated, systematic tutorial – with clearly spelled-out and unified nomenclature – derived from the author’s own modeling efforts, publications and teaching over half a century. Ambiguities in some concepts and tools are clarified and others are rendered more accessible and practical. The latter include novel qualitative theory and methodologies for recognizing dynamical signatures in data using structural (multicompartmental and network) models and graph theory; and analyzing structural and measurement (data) models for quantification feasibility. The level is basic-to-intermediate, with much emphasis on biomodeling from real biodata, for use in real applications. Introductory coverage of core mathematical concepts such as linear and nonlinear differential and difference equations, Laplace transforms, linear algebra, probability, statistics and stochastics topics; PLUS ....... The pertinent biology, biochemistry, biophysics or pharmacology for modeling are provided, to support understanding the amalgam of “math modeling” with life sciences. Strong emphasis on quantifying as well as building and analyzing biomodels: includes methodology and computational tools for parameter identifiability and sensitivity analysis; parameter estimation from real data; model distinguishability and simplification; and practical bioexperiment design and optimization. Companion website provides solutions and program code for examples and exercises using Matlab, Simulink, VisSim, SimBiology, SAAMII, AMIGO, Copasi and SBML-coded models. A full set of PowerPoint slides are available from the author for teaching from his textbook. He uses them to teach a 10 week quarter upper division course at UCLA, which meets twice a week, so there are 20 lectures. They can easily be augmented or stretched for a 15 week semester course. Importantly, the slides are editable, so they can be readily adapted to a lecturer’s personal style and course content needs. The lectures are based on excerpts from 12 of the first 13 chapters of DSBMS. They are designed to highlight the key course material, as a study guide and structure for students following the full text content. The complete PowerPoint slide package (~25 MB) can be obtained by instructors (or prospective instructors) by emailing the author directly, at: [email protected]



Computational Biology

Computational Biology Author Röbbe Wünschiers
ISBN-10 9783642185526
Release 2012-12-06
Pages 284
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-Teaches the reader how to use Unix, which is the key to basic computing and allows the most flexibility for bioinformatics applications -Written specifically with the needs of molecular biologists in mind -Easy to follow, written for beginners with no computational knowledge -Includes examples from biological data analysis -Can be use either for self-teaching or in courses



Computational Modeling of Genetic and Biochemical Networks

Computational Modeling of Genetic and Biochemical Networks Author James M. Bower
ISBN-10 0262524236
Release 2001
Pages 336
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How new modeling techniques can be used to explore functionally relevant molecular and cellular relationships.



Gene Expression Programming

Gene Expression Programming Author Candida Ferreira
ISBN-10 9783540328490
Release 2006-08-29
Pages 480
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This book describes the basic ideas of gene expression programming (GEP) and numerous modifications to this powerful new algorithm. It provides all the implementation details of GEP so that anyone with elementary programming skills will be able to implement it themselves. The book includes a self-contained introduction to this new exciting field of computational intelligence. This second edition has been revised and extended with five new chapters.



Computational Modeling and Simulation of Intellect Current State and Future Perspectives

Computational Modeling and Simulation of Intellect  Current State and Future Perspectives Author Igelnik, Boris
ISBN-10 9781609605520
Release 2011-05-31
Pages 686
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"This book confronts the problem of meaning by fusing together methods specific to different fields and exploring the computational efficiency and scalability of these methods"--Provided by publisher.