Introduction to Computational Genomics: A Case Studies Approach

by Nello Cristianini

Where did SARS come from? Have we inherited genes from Neanderthals? How do plants use their internal clock? The genomic revolution in biology enables us to answer such questions. But the revolution would have been impossible without the support of powerful computational and statistical methods that enable us to exploit genomic data. Many universities are introducing courses to train the next generation of biologists fluent in mathematics and computer science, and data analysts familiar with biology. This readable and entertaining book, based on successful taught courses, provides a roadmap to navigate entry to this field. It guides the reader through key achievements of bioinformatics, using a hands-on approach. Statistical sequence analysis, sequence alignment, hidden Markov models, gene and motif finding and more, are introduced in a rigorous yet accessible way. A companion website provides the reader with Matlab-related software tools for reproducing the steps demonstrated in the book.

Genres: Computer Science, Nonfiction

197 pages, Kindle Edition

First published December 30, 2002

About the author

Nello Cristianini is a professor of Artificial Intelligence in the Department of Computer Science at the University of Bath.

His research contributions encompass the fields of machine learning, artificial intelligence and bioinformatics. Particularly, his work has focused on statistical analysis of learning algorithms, to its application to support vector machines, kernel methods and other algorithms. Cristianini is the co-author of two widely known books in machine learning, An Introduction to Support Vector Machines and Kernel Methods for Pattern Analysis and a book in bioinformatics, "Introduction to Computational Genomics".

Recent research has focused on the philosophical challenges posed by modern artificial intelligence, big-data analysis of newspapers content, the analysis of social media content. Previous research had focused on statistical pattern analysis; machine learning and artificial intelligence; machine translation; bioinformatics.
As a practitioner of data-driven AI and Machine Learning, Cristianini frequently gives public talks about the need for a deeper ethical understanding of the effects of modern data-science on society.
Cristianini is a recipient of the Royal Society Wolfson Research Merit Award and of a European Research Council Advanced Grant.

Reviews

[Friend of the Talking Bird]

Genomics is now a separate academic discipline (for example, it has its own department at the University of Washington, like statistics), and there are many cool applications of computer science to its problems: dynamic programming-based algorithms for comparing sequences of codons, a greedy algorithm for inferring phylogenetic trees, and so on. For me the algorithms are simple, but the problem domain isn't; perhaps for the target audience it is the other way around. I bought it because it was used for some undergraduate computer science course at my alma mater, though.

[Boštjan]

It is a good book. The author explains the basics very well and in a beginner level way, but my problem with it is that it should contain at least some algorithms in it (in pseudo-format code or in python, java etc.), or maybe a CD that goes along with it.

It's not a book for biologists, nor is it a book for computer scientists, it's stuck somewhere in between and that's something I think the author needs to address. And maybe then the book will be worth its price, because currently, at 200 pages and no code to go along with it, it is an expensive purchase.

[Michiel]

Very fun book that explains bioinformatics at the hand of 10 small case studies: study of mutations in the HIV virus, origin of SARS, internal clock of plants. Quick read but an accessible introduction to the field.

[E.J.M. Smith]

A clear, well-written introduction to the topic. Takes difficult genetic and statistical problems, and presents them in a way which is straightforward and easy to understand.

[Benji]

Toegankelijke inleiding tot een fascinerend onderzoeksgebied.