Algebraic Statistics for Computational Biology


Algebraic Statistics for Computational Biology

The quantitative analysis of biological sequence data is based on methods from statistics coupled with efficient algorithms from computer science. Algebra provides a framework for unifying many of the seemingly disparate techniques used by computational biologists. This book offers an introduction to this mathematical framework and describes tools from computational algebra for designing new algorithms for exact, accurate results. These algorithms can be applied to biological problems such as aligning genomes, finding genes and constructing phylogenies. As the first book in the exciting and dynamic area, it will be welcomed as a text for self-study or for advanced undergraduate and beginning graduate courses.


 Reviews:

"This substantial, enthusiastically presented, and confidently written book is largely based on and around a graduate course taught by the two editors, who are in the mathematics department at the University of California, Berkeley, during the fall of 2004. The four introductory chapters were written by the editors, whilst the seventeen chapters in Part II were written up as a result of research projects undertaken by course participants."
ISI Short Book Reviews

'… substantial, enthusiastically presented, and confidently written …' Publication of the International Statistical Institute

'This book is of great interest to research workers, teachers and students in applied statistics, biology, medicine and genetics.' Zentralblatt MATH

No references available.