Computer Programming in Quantitative Biology
Free Global Shipping
No minimum orderDescription
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.
Table of Contents
Preface
Chapter 1: Introduction
Chapter 2: Electronic Digital Computers
Number Systems
Decimal notation
Binary notation
Octal notation
Interconversion of number systems
Binary coded decimal
Computer Structure and Function
Input devices
Computer storage
Arithmetic unit
Output devices
Control unit
Programming Languages
Chapter 3: Synopsis of Fortran Programming
Planning a Program
FORTRAN IV
Fortran characters
Statements and lay-out
Constants
Variables
Arithmetic expressions
Mathematical functions
Other supplied functions
Arithmetic statements
STOP, PAUSE and END statements
Input—Output statements
Further FORMAT specifications
Transfer statements
Subscripted variables and the DIMENSION statement
The DO statement
Arithmetic statement functions
Function subprograms
Subroutine subprograms
Non-executable statements
Running a Program
Chapter 4: Three Simple Statistical Programs
Program 1: Computation of mean, variance, standard deviation and other statistics of a sample
Program 2: Correlation and regression
Program 3: Comparison of means of two samples
Chapter 5: Sorting, Tabulating and Summarising Data
Program 4: Sorting an array in ascending and/or descending order
Program 5: Ranking an array of numbers
Program 6: Tabulation of frequency tables
Program 7: Construction of two-way contingency tables
Program 8: Data-summarising Program 1
Program 9: Data-summarising Program 2
Program 10: Data-summarising Program 3
Program 11: Calculation of running means
Chapter 6: Analysis of Variance
Program 12: Two-factor analysis of variance without replication
Program 13: Incomplete three-factor analysis of variance (two factors with replication)
Program 14: Three-factor analysis of variance without replication
Program 15: Analysis of variance: Latin square design
Program 16: Analysis of variance: balanced incomplete block design
Chapter 7: Correlation and Regression Analysis
Program 17: Correlation and regression of data arranged in grouped frequency table
Program 18: Regression with tests of significance and linearity by analysis of variance
Program 19: Comparison of two regression lines by analysis of variance
Program 20: Autocorrelations in time-series
Program 21: Cross-correlations in time-series
Program 22: Best-fit linear functional relationship between two variables, each subject to error
Chapter 8: Matrix Methods
Program 23: Dispersion and correlation matrices
Chapter 9: Further Matrix Method
Program 24: Determinant of a matrix
Matrix Inversion
Program 25: Matrix inversion
Latent Roots and Vectors
Program 26: Latent roots and vectors of a real symmetric matrix
Program 27: Latent roots and vectors of a real non-symmetric matrix
Chapter 10: Multiple Regression and Multivariate Analysis
Program 28: Multiple linear regression analysis
Program 29: Hotelling's T2 and discriminant function for two groups
Program 30: Principal component analysis
Program 31: Multiple discriminant analysis
Chapter 11: Nonparametric Statistics
Program 32: Chi-squared test of association in two-way contingency tables
Program 33: Chi-squared test for goodness of fit
Program 34: Spearman's rank correlation coefficient
Program 35: Wilcoxon's signed ranks test
Program 36: Mann-Whitney test for two independent samples
Program 37: Kruskal-Wallis test for several independent samples
Chapter 12: Fitting Theoretical Distributions to Data
Program 38: Fitting a normal distribution and testing goodness of fit
Program 39: Fitting a Poisson distribution and testing goodness of fit
Program 40: Fitting a binomial distribution and testing goodness of fit
Program 41: Fitting a negative binomial distribution and testing goodness of fit
Chapter 13: Models and Simulation
Program 42: Numerical integration by Simpson's rule
Program 43: Solution of first-order ordinary differential equations by a Runge-Kutta method
Subroutines RAND1 to RAND7
Calculation of Probabilities from Statistic Distributions
Program 44: Computation of probabilities corresponding to the test-statistics x2t, z and F
Chapter 14: Three Special-Purpose Programs
Program 45: Probit analysis
Program 46: Single linkage cluster analysis
Program 47: Estimation of population-size by marking and recapture
Chapter 15: Efficiency in Programming
Choice of Efficient Algorithms
Economy in Computer Time
Conservation of Core Storage
Program 48: Dispersion and correlation matrices with compressed vector storage
Accuracy Considerations
Testing of Programs
Use of Available Package Programs or Subroutines
Conclusion
References
Author Index
Subject Index
Product details
- No. of pages: 504
- Language: English
- Copyright: © Academic Press 1972
- Published: November 1, 1971
- Imprint: Academic Press
- eBook ISBN: 9780323147873
About the Author
R.G. Davies
Ratings and Reviews
There are currently no reviews for "Computer Programming in Quantitative Biology"