This book provides an introductory account of probability theory, statistics and stochastic process theory appropriate to computational biology and bioinformatics. These topics are important in the analysis of human genome data.

First book on this subject written from a statistical viewpoint Includes methods important in the analysis of human genome data Only basic knowledge of biology is assumed

Autorentext

Warren Ewens is an Emeritus Professor of Biology at the University of Pennsylvania. His research interests focus on the use of Statistics in genetics, in particular in describing the evolutionary process in genetical terms and in DNA sequence analysis.Katherine Brumberg is a PhD candidate in Statistics and Data Science at the Wharton School of the University of Pennsylvania. Her research interests focus on causal inference, in particular attaining optimal covariate balance in observational studies.

Inhalt
Probability Theory (i): One Random Variable.- Probability Theory (ii): Many Random Variables.- Statistics (i): An Introduction to Statistical Inference.- Stochastic Processes (i): Poisson Processes and Markov Chains.- The Analysis of One DNA Sequence.- The Analysis of Multiple DNA or Protein Sequences.- Stochastic Processes (ii): Random Walks.- Statistics (ii): Classical Estimation Theory.- Statistics (iii): Classical Hypothesis Testing Theory.- BLAST.- Stochastic Processes (iii): Markov Chains.- Hidden Markov Models.- Gene Expression, Microarrays, and Multiple Testing.- Evolutionary Models.- Phylogenetic Tree Estimation.