Computer Programming in Quantitative Biology

Author: Davies   R. G.  

Publisher: Elsevier Science‎

Publication year: 2012

E-ISBN: 9780323147873

P-ISBN(Paperback): 9780122062506

P-ISBN(Hardback):  9780122062506

Subject: Z2 Encyclopedias, Reference Books

Language: ENG

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Description

Computer Programming in Quantitative Biology covers the general background of Fortran coding and the more sophisticated computer programs likely to be encountered in quantitative biology. It discusses the application of over 40 appropriate and easily adaptable programming techniques to problems of major biological interest.

Organized into 15 chapters, the book starts by providing an introductory outline of computer structure and function needed to appreciate many basic programming procedures. A chapter discusses some general principles underlying Fortran coding and the use of digital computers, with emphasis on major features of Fortran IV. Other chapters present short introduction to the statistical or mathematical techniques in each of the main sections under which program are described. These chapters also provide some aspects of matrix algebra that are essential for serious statistical programming and offer a general guide to efficiency in programming. All complete programs are accompanied by a flowchart and a detailed discussion.
This book is a valuable source of information for biologists, computational biologists, research biologists, undergraduate students, and advanced or specialized students of biology.

Chapter

Front Cover

pp.:  1 – 4

Copyright Page

pp.:  5 – 8

Preface

pp.:  6 – 14

Table of Contents

pp.:  8 – 6

Chapter 1. Introduction

pp.:  14 – 18

Chapter 3. Synopsis of Fortran Programming

pp.:  45 – 95

Chapter 4. Three Simple Statistical Programs

pp.:  95 – 118

Chapter 5. Sorting, Tabulating and Summarising Data

pp.:  118 – 158

Chapter 6. Analysis of Variance

pp.:  158 – 194

Chapter 7. Correlation and Regression Analysis

pp.:  194 – 229

Chapter 8. Matrix Methods

pp.:  229 – 252

Chapter 9. Further Matrix Methods

pp.:  252 – 286

Chapter 10. Multiple Regression and Multivariate Analysis

pp.:  286 – 325

Chapter 11. Nonparametric Statistics

pp.:  325 – 356

Chapter 12. Fitting Theoretical Distributions to Data

pp.:  356 – 389

Chapter 13. Models and Simulation

pp.:  389 – 423

Chapter 14. Three Special-Purpose Programs

pp.:  423 – 453

Chapter 15. Efficiency in Programming

pp.:  453 – 491

References

pp.:  491 – 496

Author Index

pp.:  496 – 499

Subject Index

pp.:  499 – 506

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