Math 338, Spring 2009: Syllabus

The chapter and section numbers listed under "text" refer to the on-line text.

	Date	Topics	Text	Assignments
1	1/20	Random sampling Intro. to Population Genetics	Chapter 1, 1.1-1.3 especially Chapter 2, Section 1	Assignment 1, due Jan. 22
2	1/22	Populations, genotype and allele frequencies random mating, infinite populations	Chapter 3, section 3.2	Assignment 2, due Jan. 29 Solutions to assignments 1 and 2
3	1/27	One locus/two allele, infinite population model Hardy-Weinberg equilibrium	Chapter 3, section 3.3
4	1/29	Difference Equations Other infinite population models	Chapter 3, Sections 3.1 and 3.3	Assignment 3, due Feb. 5 Solutions (CORRECTED ON 2/11), assignment 3
5	2/3	Nonlinear difference equations; Model with selection	Chapter 3, section 3.4
6	2/5	Model with selection; derivation and analysis	Chapter 3, section 3.4 Some corrections to Chapter 3 More corrections	Assignment 4, due Feb. 12 Corrections to Assignment 4 Solutions to Assignment 4
7	2/10	Markov chains; The Moran and Wright-Fisher Models	Chapter 4, 4.1 and 4.2
8	2/12	Wright-Fisher Model Calculating distributions of Markov chains	Chapter 4 with 4.3	Assignment 5, due Feb. 19 Solutions to Assignment 5
9	2/17	Markov chains with absorbtion; Invariant measures	Chapter 4, 4.3
10	2/19	Markov chains with recurrent states	Chapter 4, section 4.4(link to entire chapter)	Assignment 6, due Feb. 26 Solutions to Assignment 6 Solutions to 5.1, 5.4
11	2/24	Coverage models. Expected number of contigs; Random fragment lengths.	Chapter 5, Section 5.2
12	2/26	Coverage models, continued	Chapter 5, Section 5.2
13	3/3	First Midterm	Open book and notes,
14	3/5	Restriction Enzyme digests Poisson processes; introduction	Chapter 5, section 5.2 up to page 22, section 5.3	Problems due 03/12 Solutions to Assignment 7
15	3/10	Poisson processes; Interarrival times, summing and thinning. Application to restriction enzyme digests.	Chapter 5, sections 5.3 and 5,4
16	3/12	Poisson processes; current and residual life, gamma distribution Restriction enzyme library coverage	Chapter 5, sections 5.3 and 5.4
17	3/24	Parametric models; likelihood function; Maximum Likelihood estimation	Chapter 6, 6.1, 6.2, 6.3	Problems due 3/26: 5.26,5.28, 5.29 Hand in 5.28 Solutions to Assignment 8
18	3/26	Hypothesis testing	Chapter 6, 6.3, 6.4	Problems, due 4/2 Solutions to Assignment 9
19	3/31	Hypothesis testing: log-likelihood tests, p-values, Testing the Markov chain hypothesis	Chapter 6, 6.4 and 6.5
20	4/2	Testing IID sites versus Markov models; Introduction to the alignment problem	Chapter 6, sections 6.6, 6.7
21	4/7	Scoring alignments Introduction to dynamic programming	Chapter 6, 6.7; Chapter 7, 7.1	Assignment 10, due 4/9 Solutions(corrected 4/23), Assignment 10
22	4/9	Test review; BLOSUM substitution matrices	Chapter 6, 6.7
23	4/14	Second Midterm
24	4/16	Optimal alignment; linear gap penalty case	Chapter 7	Assignment 11, due 4/23 Solutions, Assignment 11 Example of repeat match algorithm Example of backward dynamic programming
25	4/21	Optimal local and overlap alignment	Chapter 7
26	4/23	Repeat Match Alignment Hidden Markov models; introduction	Chapter 8	Assignment 12, due April 30 Solutions, Assignment 12
27	4/28	Hidden Markov models; forward and Viterbi algorithms	Chapter 8
28	4/30	HMM problem solutions; Final Exam Review
	5/9	NOTE CHANGE!: FINAL EXAM, MAY 8, 12-3, SEC 220