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Introduction to bioinformatics
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Author:
Arthur Mallay LeskNumber Of Downloads:
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Language:
English
File Size:
6.49 MB
Category:
TechnologySection:
Pages:
268
Quality:
excellent
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1300
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Book Description
Introduction to Bioinformatics by Arthur Lesk is a timely and much-needed textbook which provides an accessible and thorough introduction to a subject which is becoming a fundamental part of biological science today. As a pioneer of the use of bioinformatics techniques in research, Dr Lesk brings unrivalled experience and expertise to the study of this field. The aim of the book is to generate an understanding of the biological background of bioinformatics, and to integrate this with an introduction to the use of computational skills. Without describing computer science or sophisticated programming skills in detail, the book supports and encourages the application of the many powerful computational tools of bioinformatics in a way that is both relevant to and stimulating for the reader.
The book contains numerous problems and innovative Weblems (for Web-based Problems) to encourage students to engage with the subject and with the accompanying web site and to develop a working understanding and appreciation of the power of bioinformatics as a research tool.
Arthur Mallay Lesk
Arthur Mallay Lesk, is a protein science researcher, who is a professor of biochemistry and molecular biology at the Pennsylvania State University in University Park. Lesk received a bachelor's degree, magna cum laude, from Harvard University in 1961. He received his doctoral degree from Princeton University in 1966. He also received a master's degree from the University of Cambridge in the United Kingdom in 1999. Lesk has made significant contributions to the study of protein evolution. He and Cyrus Chothia, working at the Medical Research Council (UK) Laboratory of Molecular Biology in Cambridge, United Kingdom, discovered the relationship between changes in amino-acid sequence and changes in protein structure by analyzing the mechanism of evolution in protein families.This discovery has provided the quantitative basis for the most successful and widely used method of structure prediction, known as homology modelling.
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