Medienkombination, Englisch, 328 Seiten, Buch mit CD-ROM, Format (B × H): 170 mm x 244 mm, Gewicht: 1450 g
An Evolutionary Approach
Medienkombination, Englisch, 328 Seiten, Buch mit CD-ROM, Format (B × H): 170 mm x 244 mm, Gewicht: 1450 g
ISBN: 978-3-7643-6700-8
Verlag: Springer
Analysis of molecular sequence data is the main subject of this introduction to computational biology. There are two closely connected aspects to biological sequences: (i) their relative position in the space of all other sequences, and (ii) their movement through this sequence space in evolutionary time. Accordingly, the first part of the book deals with classical methods of sequence analysis: pairwise alignment, exact string matching, multiple alignment, and hidden Markov models. In the second part evolutionary time takes center stage and phylogenetic reconstruction, the analysis of sequence variation, and the dynamics of genes in populations are explained in detail. In addition, the book contains a computer program with a graphical user interface that allows the reader to experiment with a number of key concepts developed by the authors.
This textbook is intended for students enrolled in courses in computational biology or bioinformatics as well as for molecular biologists, mathematicians, and computer scientists.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik
- Mathematik | Informatik EDV | Informatik Informatik
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik
- Naturwissenschaften Biowissenschaften Molekularbiologie
- Naturwissenschaften Biowissenschaften Biowissenschaften Evolutionsbiologie
Weitere Infos & Material
Sequences in Space.- Optimal Pairwise Alignment.- Biological Sequences and the Exact String Matching Problem.- Fast Alignment: Genome Comparison and Database Searching.- Multiple Sequence Alignment.- Sequence Profiles and Hidden Markov Models.- Gene Prediction.- Sequences in Time.- Phylogeny.- Sequence Variation and Molecular Evolution.- Genes in Populations: Forward in Time.- Genes in Populations: Backward in Time.- Testing Evolutionary Hypotheses.
