Computational Molecular Biology and Genomics Reading

Texts

There is no required textbook. No single textbook covers all of the material covered in the course. Reading materials drawn from several textbooks, as well as the primary literature, will be available through the library's electronic reserve system and links from this page. Electronic materials are available on the cmu.edu subnet only.

The Cartoon Guide to Genetics, by Larry Gonick and Mark Wheelis, is recommended for those needing additional biological background. It is available in the campus bookstore.

For supplementary reading, the following textbooks are recommended:

Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids, R. Durbin et al.
Introduction to Computational Molecular Biology, J.C. Setubal and J. Meidanis
Bioinformatics: Sequence and Genome Analysis, D.W. Mount.
Statistical Methods in Bioinformatics: An Introduction Ewens and Grant.

These books will be on reserve in both the Mellon and Engineering libraries.

Readings by topic

For those who wish to read the material before class, reading assignments are listed below. Topics will not necessarily be covered in the order given.

TOPIC ASSIGNED READING ADDITIONAL TOPICS

Pairwise sequence comparison
Setubal and Meidanis, 47-57, 89-98; (electronic reserve)

Durbin, pp. 17-24 (electronic reserves)

Saving space, Setubal and Meidanis, 58-60; (physical reserve)

General and affine gap penalty functions, Setubal and Meidanis, 60-66 (physical reserve), Durbin, pp. 29-30 (electronic reserves)

Global multiple sequence alignment
Setubal and Meidanis, 69-72 (electronic reserve)

Durbin, 6.1 -- 6.4 (electronic reserves)

Protein multiple sequence alignment , Do and Katoh, 2008.

Strategies for multiple sequence alignment, Nicholas HB Jr, Ropelewski AJ, Deerfield DW 2nd, Biotechniques 2002 Mar;32(3):572-4 (electronic reserve)

Substitution models

Background: Markov chains

Models of nucleotide substitution

Markov Chain background
- Ewens and Grant, 4.4-4.8

- Durbin et al., 48-51 (Section 3.1) (electronic reserves)

Models of nucleotide substitution
- Durbin et al., 8.2, pp. 193 - 197 only (electronic reserves)

Amino acid substitution matrices

Substitution matrices, PAM matrices:

Setubal and Meidanis, pp. 80-84; (electronic reserve)

Mount, pp. 76-89; (electronic reserve)

Durbin et al, pp. 14-16 (electronic reserves)

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 (electronic reserve)

Database Searching
Mount, pp. 282-291 (electronic reserve)

BLAST:

Setubal and Meidanis, 84-87 (electronic reserve)

Basic local alignment search tool,Altschul et al. , J. Mol. Bio., 1990 (electronic reserve)

Gapped BLAST and PSI-BLAST: a new generation of protein database search programs, Altschul et al. ,Nucleic Acids Research, 1997, pp. 3389 - 3394 (electronic reserve)

BLAST statistics:

The statistics of sequence similarity scores S. F. Altschul
Using BLAST in practise:

Blast tutorial
Blast statistics:
Amino acid substitution matrices from an information theoretic perspective S. F. Altschul, J. Mol. Bio., 219:555-565, 1991 (electronic reserve)

A protein alignment scoring system sensitive at all evolutionary distances, S. F. Altschul, J. Mol. Evol., 36:290-300 , 1993 (electronic reserve)

Statistical Methods in Bioinformatics, W. Ewens and G. Grant (Physical reserves)

Other BLAST references

Position specific scoring matrices (PSSMs), the Gibbs sampler

Gibbs sampler
Ewens and Grant, pp. 211-215. (electronic reserve).

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

Hidden Markov Models
Local multiple sequence alignment

Ewens & Grant, pp 327-340 (electronic reserve)

Durbin et al, 3.1 - 3.4 (electronic reserves)

Mount, pp 161-198 (physical reserve) Pseudocounts:

Durbin, et al: 5.6(electronic reserves)
Hidden Markov Models in Computational Biology: Applications to Protein Modeling,
Krogh et al., JMB 235, pp 1501--1531,(1994).
Available through electronic reserves.

Applications of HMMs to molecular biology
Durbin et al, 5.1 - 5.4 and pp 149-154, 158 (electronic reserves)

Hidden Markov Models in Computational Biology, Krogh et al., JMB,235, 1501-1531, 1994 (electronic reserve)

Return to course homepage

Last modified: August 6th, 2018.
Maintained by Dannie Durand (durand@cs.cmu.edu).

TOPIC	ASSIGNED READING	ADDITIONAL TOPICS
Pairwise sequence comparison	Setubal and Meidanis, 47-57, 89-98; (electronic reserve) Durbin, pp. 17-24 (electronic reserves)	Saving space, Setubal and Meidanis, 58-60; (physical reserve) General and affine gap penalty functions, Setubal and Meidanis, 60-66 (physical reserve), Durbin, pp. 29-30 (electronic reserves)
Global multiple sequence alignment	Setubal and Meidanis, 69-72 (electronic reserve) Durbin, 6.1 -- 6.4 (electronic reserves) Protein multiple sequence alignment , Do and Katoh, 2008.	Strategies for multiple sequence alignment, Nicholas HB Jr, Ropelewski AJ, Deerfield DW 2nd, Biotechniques 2002 Mar;32(3):572-4 (electronic reserve)
Substitution models Background: Markov chains Models of nucleotide substitution	Markov Chain background - Ewens and Grant, 4.4-4.8 - Durbin et al., 48-51 (Section 3.1) (electronic reserves) Models of nucleotide substitution - Durbin et al., 8.2, pp. 193 - 197 only (electronic reserves)
Amino acid substitution matrices	Substitution matrices, PAM matrices: Setubal and Meidanis, pp. 80-84; (electronic reserve) Mount, pp. 76-89; (electronic reserve) Durbin et al, pp. 14-16 (electronic reserves) 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 (electronic reserve)
Database Searching	Mount, pp. 282-291 (electronic reserve) BLAST: Setubal and Meidanis, 84-87 (electronic reserve) Basic local alignment search tool,Altschul et al. , J. Mol. Bio., 1990 (electronic reserve) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs, Altschul et al. ,Nucleic Acids Research, 1997, pp. 3389 - 3394 (electronic reserve) BLAST statistics: The statistics of sequence similarity scores S. F. Altschul Using BLAST in practise: Blast tutorial	Blast statistics: Amino acid substitution matrices from an information theoretic perspective S. F. Altschul, J. Mol. Bio., 219:555-565, 1991 (electronic reserve) A protein alignment scoring system sensitive at all evolutionary distances, S. F. Altschul, J. Mol. Evol., 36:290-300 , 1993 (electronic reserve) Statistical Methods in Bioinformatics, W. Ewens and G. Grant (Physical reserves) Other BLAST references
Position specific scoring matrices (PSSMs), the Gibbs sampler	Gibbs sampler Ewens and Grant, pp. 211-215. (electronic reserve).	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
Hidden Markov Models Local multiple sequence alignment	Ewens & Grant, pp 327-340 (electronic reserve) Durbin et al, 3.1 - 3.4 (electronic reserves)	Mount, pp 161-198 (physical reserve) Pseudocounts: Durbin, et al: 5.6(electronic reserves) Hidden Markov Models in Computational Biology: Applications to Protein Modeling, Krogh et al., JMB 235, pp 1501--1531,(1994). Available through electronic reserves.
Applications of HMMs to molecular biology	Durbin et al, 5.1 - 5.4 and pp 149-154, 158 (electronic reserves) Hidden Markov Models in Computational Biology, Krogh et al., JMB,235, 1501-1531, 1994 (electronic reserve)