| Author: | Sunil K. Mathur | ISBN: | 9780123751058 |
| Publisher: | Elsevier Science | Publication: | December 21, 2009 |
| Imprint: | Academic Press | Language: | English |
| Author: | Sunil K. Mathur |
| ISBN: | 9780123751058 |
| Publisher: | Elsevier Science |
| Publication: | December 21, 2009 |
| Imprint: | Academic Press |
| Language: | English |
Statistical Bioinformatics provides a balanced treatment of statistical theory in the context of bioinformatics applications.
Designed for a one or two semester senior undergraduate or graduate bioinformatics course, the text takes a broad view of the subject – not just gene expression and sequence analysis, but a careful balance of statistical theory in the context of bioinformatics applications.
The inclusion of R & SAS code as well as the development of advanced methodology such as Bayesian and Markov models provides students with the important foundation needed to conduct bioinformatics.
- Integrates biological, statistical and computational concepts
- Inclusion of R & SAS code
- Provides coverage of complex statistical methods in context with applications in bioinformatics
- Exercises and examples aid teaching and learning presented at the right level
- Bayesian methods and the modern multiple testing principles in one convenient book
Statistical Bioinformatics provides a balanced treatment of statistical theory in the context of bioinformatics applications.
Designed for a one or two semester senior undergraduate or graduate bioinformatics course, the text takes a broad view of the subject – not just gene expression and sequence analysis, but a careful balance of statistical theory in the context of bioinformatics applications.
The inclusion of R & SAS code as well as the development of advanced methodology such as Bayesian and Markov models provides students with the important foundation needed to conduct bioinformatics.
- Integrates biological, statistical and computational concepts
- Inclusion of R & SAS code
- Provides coverage of complex statistical methods in context with applications in bioinformatics
- Exercises and examples aid teaching and learning presented at the right level
- Bayesian methods and the modern multiple testing principles in one convenient book
