640:338:01 Discrete and Probabilistic Models in Biology
COURSE NOTES by Daniel Ocone

This page contains links to a text in probabilistic and dynamic programming models for applications to biology. They are made available here free for private study. Otherwise the author reserves copyright privileges. Please send any comments or corrections to ocone@math.rutgers.edu.

1. Chapter 1, Heredity, Genes, and DNA; 25 page pdf file, last revised, June, 2016.

A brief introduction to relevant biological concepts. Contents:

2. Chapter 2, Probability Theory; pdf file, revised January 2014

A review of basic probability, with a focus on what is used in the text and on examples relevant to biological models.

3. Chapter 3, Population Genetics for Large Populations; revised January, 2014

4. Markov Chains and Applications to Population Genetics; revised, March 2014

5. Chapter 5, Probabilistic Analysis of Sequencing Problems; 34 page pdf file, March 2014.

6. Chapter 6, Maximum Likelihood Estimation and Hypothesis Testing ; 24 page pdf file, March 27, 2006

Corrections to Chapter 6, April 18, 2005. (These corrections are already made on the version posted March 27, 2006.)

7. Chapter 7, Sequence Alignment by Dynamic Programming; Sections, 7.1, 7.2.1-7.2.4. 22 page pdf file; Sections 7.2.5--7.2.8 19 page pdf file.

8. Chapter 8, Hidden Markov Models; 26 page pdf file, April 18, 2005.