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Books in Mathematical biosciences

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21-28 of 28 results in All results

Computer Methods Part B

  • 1st Edition
  • Volume 467
  • November 5, 2009
  • Michael L. Johnson + 1 more
  • English
  • Hardback
    9 7 8 - 0 - 1 2 - 3 7 5 0 2 3 - 5
  • eBook
    9 7 8 - 0 - 0 8 - 0 9 6 2 8 0 - 1
The combination of faster, more advanced computers and more quantitatively oriented biomedical researchers has recently yielded new and more precise methods for the analysis of biomedical data. These better analyses have enhanced the conclusions that can be drawn from biomedical data, and they have changed the way that experiments are designed and performed. This volume, along with previous and forthcoming Computer Methods volumes for the Methods in Enzymology serial, aims to inform biomedical researchers about recent applications of modern data analysis and simulation methods as applied to biomedical research.

Probabilistic Methods for Bioinformatics

  • 1st Edition
  • April 3, 2009
  • Richard E. Neapolitan
  • English
  • Hardback
    9 7 8 - 0 - 1 2 - 3 7 0 4 7 6 - 4
  • eBook
    9 7 8 - 0 - 0 8 - 0 9 1 9 3 6 - 2
The Bayesian network is one of the most important architectures for representing and reasoning with multivariate probability distributions. When used in conjunction with specialized informatics, possibilities of real-world applications are achieved. Probabilistic Methods for BioInformatics explains the application of probability and statistics, in particular Bayesian networks, to genetics. This book provides background material on probability, statistics, and genetics, and then moves on to discuss Bayesian networks and applications to bioinformatics. Rather than getting bogged down in proofs and algorithms, probabilistic methods used for biological information and Bayesian networks are explained in an accessible way using applications and case studies. The many useful applications of Bayesian networks that have been developed in the past 10 years are discussed. Forming a review of all the significant work in the field that will arguably become the most prevalent method in biological data analysis.

In Silico

  • 1st Edition
  • July 1, 2008
  • Jason Sharpe + 2 more
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 8 7 9 2 5 - 3
In Silico introduces Maya programming into one of the most fascinating application areas of 3D graphics: biological visualization. In five building-block tutorials, this book prepares animators to work with visualization problems in cell biology. The book assumes no deep knowledge of cell biology or 3D graphics programming. An accompanying DVD-ROM includes code derived from the tutorials, the working Maya computer files, and sample animated movies.

Systems Biology

  • 1st Edition
  • March 20, 2007
  • Fred Boogerd + 3 more
  • English
  • Hardback
    9 7 8 - 0 - 4 4 4 - 5 2 0 8 5 - 2
  • eBook
    9 7 8 - 0 - 0 8 - 0 4 7 5 2 7 - 1
Systems biology is a vigorous and expanding discipline, in many ways a successor to genomics and perhaps unprecedented in its combination of biology with a great many other sciences, from physics to ecology, from mathematics to medicine, and from philosophy to chemistry. Studying the philosophical foundations of systems biology may resolve a longer standing issue, i.e., the extent to which Biology is entitled to its own scientific foundations rather than being dominated by existing philosophies.

Biostatistics

  • 2nd Edition
  • December 14, 2006
  • Ronald N. Forthofer + 2 more
  • English
  • Hardback
    9 7 8 - 0 - 1 2 - 3 6 9 4 9 2 - 8
  • eBook
    9 7 8 - 0 - 0 8 - 0 4 6 7 7 2 - 6
Biostatistics, Second Edition, is a user-friendly guide on biostatistics, which focuses on the proper use and interpretation of statistical methods. This textbook does not require extensive background in mathematics, making it user-friendly for all students in the public health sciences field. Instead of highlighting derivations of formulas, the authors provide rationales for the formulas, allowing students to grasp a better understanding of the link between biology and statistics. The material on life tables and survival analysis allows students to better understand the recent literature in the health field, particularly in the study of chronic disease treatment. This updated edition contains over 40% new material with modern real-life examples, exercises, and references, including new chapters on Logistic Regression, Analysis of Survey Data, and Study Designs. The book is recommended for students in the health sciences, public health professionals, and practitioners.

Mathematical Modeling for System Analysis in Agricultural Research

  • 1st Edition
  • March 27, 2003
  • K. Vohnout
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 5 3 5 8 8 - 3
This book provides a clear picture of the use of applied mathematics as a tool for improving the accuracy of agricultural research. For decades, statistics has been regarded as the fundamental tool of the scientific method. With new breakthroughs in computers and computer software, it has become feasible and necessary to improve the traditional approach in agricultural research by including additional mathematical modeling procedures.The difficulty with the use of mathematics for agricultural scientists is that most courses in applied mathematics have been designed for engineering students. This publication is written by a professional in animal science targeting professionals in the biological, namely agricultural and animal scientists and graduate students in agricultural and animal sciences. The only prerequisite for the reader to understand the topics of this book is an introduction to college algebra, calculus and statistics. This is a manual of procedures for the mathematical modeling of agricultural systems and for the design and analyses of experimental data and experimental tests. It is a step-by-step guide for mathematical modeling of agricultural systems, starting with the statement of the research problem and up to implementing the project and running system experiments.

Computational Methods in Molecular Biology

  • 1st Edition
  • Volume 32
  • June 19, 1998
  • S.L. Salzberg + 2 more
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 8 6 0 9 3 - 0
Computational biology is a rapidly expanding field, and the number and variety of computational methods used for DNA and protein sequence analysis is growing every day. These algorithms are extremely valuable to biotechnology companies and to researchers and teachers in universities.This book explains the latest computer technology for analyzing DNA, RNA, and protein sequences. Clear and easy to follow, designed specifically for the non-computer scientist, it will help biologists make better choices on which algorithm to use. New techniques and demonstrations are elucidated, as are state-of-the-art problems, and more advanced material on the latest algorithms.The primary audience for this volume are molecular biologists working either in biotechnology companies or academic research environments, individual researchers and the institutions they work for, and students. Any biologist who relies on computers should want this book.A secondary audience will be computer scientists developing techniques with applications in biology.An excellent reference for leading techniques, it will also help introduce computer scientists to the biology problems. This is an outstanding work which will be ideal for the increasing number of scientists moving into computational biology.

Vapour–Liquid Equilibrium Data at Normal Pressures

  • 1st Edition
  • January 1, 1968
  • Eduard Hála + 2 more
  • English
  • eBook
    9 7 8 - 1 - 4 8 3 1 - 5 9 1 2 - 6
Vapour-Liquid Equilibrium Data at Normal Pressures presents the direct experimental data of a set of selected systems and correlates the data with the aid of equations expressing the dependence of the activity coefficients or separation functions on the composition of the liquid phase. In the last columns of the tables, the deviations of the calculated from the direct experimental data are presented which give information on the quality of the data and on the flexibility of the correlation relations used. The text also describes the correlation of data in two-, three-, four-, and more than four-component systems.

Related subjects

Computational biology

Theoretical biology