Evolution after Gene Duplication
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Product details
- ISBN 9780470593820
- Weight: 785g
- Dimensions: 185 x 262mm
- Publication Date: 27 Oct 2010
- Publisher: John Wiley and Sons Ltd
- Publication City/Country: GB
- Product Form: Hardback
Key Features:
- Explores comparative genomics, genome evolution studies and analysis of multi-gene families such as Hox, globins, olfactory receptors and MHC (immune system)
- A complete post-genome treatment of the topic originally covered by Ohno's 1970 classic, this volume extends coverage to include the fate of associated regulatory pathways
- Taps the significant increase in multi-gene family data that has resulted from comparative genomics
- Comprehensive coverage that includes opposing theoretical viewpoints, comparative genomics data, theoretical and empirical evidence and the role of bioinformatics in the study of gene duplication
This up-to-date overview of theory and mathematical models along with practical examples is suitable for scientists across various levels of biology as well as instructors and graduate students.
Katharina Dittmar de la Cruz holds both a Ph.D. in Molecular Parisitology and Entomology and a doctorate in Veterinary Medicine, both from the University of Leipzig, Germany. An expert in phylogenetics, molecular evolution, and bioinformatics, she has recently turned her attention toward examining the implications of evolutionary forces on drug design. Dr. Dittmar is an Assistant Professor at the SUNY University at Buffalo.
David Liberles earned his Ph.D. in Chemistry at the California Institute of Technology working on the biochemsitry of nucleic acids. Subsequently, he has developed significant expertise in bioinformatics, computational biology and functional genomics. His broad experience includes a professorship at the Stockholm Bioinformatics Center and consultancies with Novo Nordisk and other private research and diagnostic companies. Currently he is Vice-Director of the University of Wyoming Bioinformatics Center and Assistant Professor of Molecular Biology.
