03511/03711 - Syllabus

Computational Molecular Biology and Genomics - Syllabus, Fall 2023

The materials in the "Assigned Reading" column are directly related to the topics covered in class. Readings under "Additional Topics" are strictly optional and will not be covered on the exams.

In some cases, the same material is covered in more than one textbook. You have the choice of selecting the text that presents a treatment of the material most to your liking. It is your responsibility to make sure that you understand the material covered in class and you may read as many or as few of these texts needed to achieve that goal.

Access to full Lecture Notes

CLASS	DATE	TOPICS	ASSIGNED READING	ADDITIONAL TOPICS
1.	Aug. 29	Introduction Pairwise sequence alignment (lecture notes, pp. 1 - 13)	Review biology and algorithms background
2.	Aug. 31	Global pairwise sequence alignment, class notes pp. 1-9 Alignment examples similarity scoring. distance scoring.	Global pairwise alignment - Setubal and Meidanis, 47-57, 89-92, 96-98; - Durbin, 17-24	Saving space, - Setubal and Meidanis, 58-60; (physical reserve) General and affine gap penalty functions, - Setubal and Meidanis, 60-66 (physical reserve) - Durbin, 29-30 Semi-global alignment - Setubal and Meidanis, 56-57,
3.	Sep. 5	Local pairwise alignment Local alignment examples. Expected alignment scores	Local pairwise alignment - Setubal and Meidanis, p. 55, - Durbin, 23-24
4.	Sep. 7	Introdution to Markov chains, class notes Sections 2.1, 2.2.1 - 2.2.3	Markov Chain background - Ewens and Grant, 4.4-4.8 - Durbin et al., 48-51 (Section 3.1)
5.	Sep. 12	Markov models of sequence evolution (lecture notes, Section 2.3) Today's slides	Models of nucleotide substitution - Durbin et al., 8.2, pp. 193 - 197 only
6.	Sep. 14	Markov models of sequence evolution, applications of DNA substitution models (lecture notes, Sections 2.3 and 2.4)
7.	Sep. 19	Markov models of sequence evolution, applications of DNA substitution models (lecture notes, Sections 2.4) Today's slides
8.	Sep. 21	Log-odds scoring
9.	Sep. 26	Amino acid substitution matrices: PAM matrices (lecture notes, Section 3.2)	Substitution matrices: - Setubal and Meidanis, 80-84; - Mount, pp. 76-89; - Durbin et al, pp. 14-16
10.	Sep. 28	Amino acid substitution matrices: PAM matrices (lecture notes, Section 3.2) PAM250, PAM30
11.	Oct. 3	Substitution matrices, continued. BLOSUM62 Today's slides	BLOSUM Matrices: - Ewens and Grant, 6.5.2. - Amino acid substitution matrices from protein blocks, Henikoff S, Henikoff JG., PNAS 89(22):10915-9, 1992
12.	Oct. 5	Motifs, local multiple sequence alignment, PSSMs
13.	Oct. 10	In-class EXAM - This exam is closed book. You may bring two pages (or one page, front and back) of your own notes. - The exam covers material covered in Lectures 1 through 7. Study Guide
14.	Oct. 12	Motifs, local multiple sequence alignment, PSSMs PSSM class notes: Section 4.1 PSSM examples pseudocount: b=1 pseudocount: b=0.1 Today's slides	Gibbs sampler Ewens and Grant, 211-215.
	Oct. 17 & Oct. 19	Mid semester break, NO CLASS.
15.	Oct. 24	Gibbs Sampler	Gibbs sampler Lecture notes, Sec 4.2 Ewens and Grant, 211-215.	Theoretical framework, convergence proofs - Ewens and Grant, 10.5.2, (physical reserves). - Detecting subtle sequence signals: a Gibbs sampling strategy for multiple alignment, Lawrence et al., Science. 1993 262(5131):208-14. - Explaining the Gibbs sampler, G. Casella & E. I. George, The American Statistician, 46:167-174, 1992
16.	Oct. 26	Gibbs Sampler continued
17.	Oct. 31	Hidden Markov Models Lecture Notes, Chapter 5
18.	Nov. 2	Designing HMMs: topology and parameter estimation with labeled sequences Today's slides	HMM Design - Durbin et al, Section 3.4, HMM model structure 68 - 71 - Lecture notes, Section 5.6, pp. 104-108
	Nov. 7	Election Day; No class
19.	Nov. 9	HMMs: Recognition algorithms Today's slides Viterbi example, Forward example.	Viterbi, Forward, Backward algorithms - Durbin et al, 55 - 61 - Ewens and Grant, 329-332
20.	Nov. 14	HMMs: the Backward Algorithm, posterior decoding, Baum-Welch	Parameter estimation, Baum-Welch algorithm Durbin et al, 61-71 Ewens & Grant, 329-332
21.	Nov. 16	Profile HMMs	Profile HMMs Durbin et al, 100-110 Multiple alignment using HMMs Ewens & Grant, 335 - 339	Tutorial on Hidden Markov Models, L.R. Rabiner, Proc. IEEE, 1989
22.	Nov. 21	Profile HMMs; Multiple alignment using Profile HMMs. Lecture notes, section 5.7
	Nov. 23	Thanksgiving Holiday: No class
23.	Nov. 28	Searching sequence databases The Basic Local Alignment Search Tool (Blast).	Blast 1990 - Setubal and Meidanis, 84-87 - Basic local alignment search tool, Altschul et al. , J. Mol. Bio., 1990
24.	Nov. 30	Blast Statistics Today's slides	Blast statistics and data base searching: - The statistics of sequence similarity scores S. F. Altschul - Amino acid substitution matrices from an information theoretic perspective, S. F. Altschul, J. Mol. Bio., 219:555-565, 1991 . - A protein alignment scoring system sensitive at all evolutionary distances, S. F. Altschul, J. Mol. Evol., 36:290-300, 1993.
25.	Dec. 5	The statistics of database searching Today's slides
26.	Dec. 7	Blast statistics continued, Today's slides
Final exam	Dec 14 1pm- 4pm WEH 7500	Final exam The exam covers the entire semester, but with a strong emphasis on the last third of the course. Study Guide	The time and date of the final exam are determined by the registrar's office and are beyond my control. You must take the final exam at the time scheduled.	Until the date of the final is determined, you should not make plans to leave for winter vacation before the end of the exam period.

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Last modified: Dec 07, 2023.