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  CSE P590B,  Sp '11:  Approximate Schedule
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Schedule details will evolve as we go; check back periodically to see the latest updates. Items in light font are more tentative than average.

    Due Lecture Topic Reading
Week 1
3/28-4/1		 Th   Introduction & Overview See hw#1.
Week 2
4/4-4/8		 Th HW #1 Sequence Alignment, Search & Scoring Durbin Ch 1-2; Papers Below
Week 3
4/11-4/15		 Th  
Week 4
4/18-4/22		 Th HW #2 Sequence Motif Modeling & Discovery: MLE & the EM Algorithm Durbin Ch 11 (excl Mix. of Dirchlets, Est. Priors in 11.5; skim 11.6); Papers Below
Week 5
4/25-4/29		 Th   Sequence Motif Modeling & Discovery: MEME & Gibbs Sampling
Week 6
5/2-5/6		 Th   HMMs & Gene Finding Durbin Ch 3-5; Papers Below
Week 7
5/9-5/13		 Th HW #3
Week 8
5/16-5/20		 Th  
Week 9
5/23-5/27		 Th HW #4 RNA Structure, Alignment, & Search Durbin Ch 9-10; Papers Below
Week 10
5/30-6/3		 Th  
Week 11
6/6-6/10		 Th HW #5 (Due Tu) No Class

Textbook:

  1. Richard Durbin, Sean R. Eddy, Anders Krogh and Graeme Mitchison, Biological Sequence Analysis: Probabilistic models of proteins and nucleic acids, Cambridge, 1998.  (Available from U Book Store, Amazon, etc.)  Errata.

References:  As we go forward, I will be updating this list and explicitly designating some of these papers as assigned reading. The rest are optional---good supplementary references, recommended if you want more depth in any of the areas.

Most links below take you to PubMed, the NIH bibliographic database. Usually, but counterintuitively, from a PubMed abstract you click the icon of the publisher (or sometimes the icon saying "UW article online") to get to the actual article.

padlock  Electronic access to journals is generally free from on-campus computers. For off-campus access, follow the "[offcampus]" links or look at the library "proxy server" instructions.  padlock

References -- Introduction & Overview: Read #2; a bit dated, but a good overview. Optional: If you want more biology, #3 is in some ways a book-length expansion of #2; I haven't read it, but the portions I've samples are good. Former students have recommended Gonick, (also a bit dated, but cheap). Alberts is a popular undergrad textbook, very comprehensive and very well written.

  1. Lawrence Hunter, "Molecular Biology for Computer Scientists," Chapter 1 of Artificial Intelligence and Molecular Biology Lawrence Hunter, ed. AAAI press, 1993. (Also here.)
  2. Lawrence Hunter, The Processes of Life: An Introduction to Molecular Biology, The MIT Press, 2009, ISBN 978-0262013055, 320 pages. (Amazon)
  3. Larry Gonick, Mark Wheelis, "The Cartoon Guide to Genetics" (Updated Edition, 1991) ISBN 0062730991, Collins. (Amazon)
  4. Bruce Alberts, Alexander Johnson, Julian Lewis, Martin Raff, Keith Roberts, Peter Walter, "Molecular Biology of the Cell", Fifth Edition, 2007, ISBN 978-0815341055, Garland, 1392 pages. (Amazon) The 4th edition of this book is available online (although the user interface leaves something to be desired).

References -- Sequence Alignment, Search & Scoring: Read #6-8. The Myers review is a bit dated, but still a good overview of algorithms and algorithmic issues.

  1. SR Eddy, "What is dynamic programming?" Nat. Biotechnol., 22, #7 (2004) 909-10. [offcampus]
  2. SR Eddy, "Where did the BLOSUM62 alignment score matrix come from?" Nat. Biotechnol., 22, #8 (2004) 1035-6. [offcampus]
  3. A Pertsemlidis, JW Fondon, "Having a BLAST with bioinformatics (and avoiding BLASTphemy)." Genome Biol., 2, #10 (2001) REVIEWS2002. [offcampus]
  4. Myers, E. (1991) "An overview of sequence comparison algorithms in molecular biology", Tech. Rep. TR-91-29, Dept. of Computer Science, Univ. of Arizona.

References -- Sequence Motif Modeling & Discovery: Read #11-13, 15. Dempster et al. is the "classic" paper on EM. Eddy is another nice, succinct intro to an important class of methods. Tompa et al. is a comprehensive comparison of several motif finding methods. Blanchette et al. is an important example of use of comparitive genomics for this problem.

  1. AP Dempster, NM Laird, DB Rubin, "Maximum Likelihood from Incomplete Data via the EM Algorithm," Journal of the Royal Statistical Society. Series B (Methodological), Vol. 39, No. 1. (1977), pp. 1-38. Available here. [offcampus]
  2. CB Do, S Batzoglou, "What is the expectation maximization algorithm?" Nat. Biotechnol., 26, #8 (2008) 897-9. [offcampus]
  3. GD Stormo, "DNA binding sites: representation and discovery." Bioinformatics, 16, #1 (2000) 16-23. [offcampus]
  4. TL Bailey, C Elkan, "Fitting a mixture model by expectation maximization to discover motifs in biopolymers." Proc Int Conf Intell Syst Mol Biol, 2, (1994) 28-36. [offcampus] Available here. See also http://meme.sdsc.edu/meme/ for related papers and resources.
  5. TL Bailey, C Elkan, "The value of prior knowledge in discovering motifs with MEME." Proc Int Conf Intell Syst Mol Biol, 3, (1995) 21-9. [offcampus]
  6. CE Lawrence, SF Altschul, MS Boguski, JS Liu, AF Neuwald, JC Wootton, "Detecting subtle sequence signals: a Gibbs sampling strategy for multiple alignment." Science, 262, #5131 (1993) 208-14. [offcampus] Available here. [offcampus]
  7. SR Eddy, "What is Bayesian statistics?" Nat. Biotechnol., 22, #9 (2004) 1177-8. [offcampus]
  8. FP Roth, JD Hughes, PW Estep, GM Church, "Finding DNA regulatory motifs within unaligned noncoding sequences clustered by whole-genome mRNA quantitation." Nat. Biotechnol., 16, #10 (1998) 939-45. [offcampus]
  9. M Tompa, N Li, TL Bailey, GM Church, B De Moor, E Eskin, AV Favorov, MC Frith, Y Fu, WJ Kent, et 15 al., "Assessing computational tools for the discovery of transcription factor binding sites." Nat. Biotechnol., 23, #1 (2005) 137-44. [offcampus]
  10. Emily Rocke and Martin Tompa An Algorithm for Finding Novel Gapped Motifs in DNA Sequences RECOMB98: Proceedings of the Second Annual International Conference on Computational Molecular Biology, New York, NY, March 1998, 228-233.
  11. M Blanchette, B Schwikowski, M Tompa, "Algorithms for phylogenetic footprinting." J. Comput. Biol., 9, #2 (2002) 211-23. [offcampus]
  12. M Blanchette, M Tompa, "FootPrinter: A program designed for phylogenetic footprinting." Nucleic Acids Res., 31, #13 (2003) 3840-2. [offcampus]

References -- HMMs & Gene Finding: Read #22, 24. The Rabiner tutorial is a very good intro to HMMs if you want a different perspective from the text. Claverie is a good survey of computational gene finding. Burget and Guigo is a careful comparison of leading programs of its day. Lander et al. and Venter are the landmark initial human genome sequence papers. Klein et al. is an interesting application of HMMs relevant to RNA gene finding, our next topic. #32, 33 are review articles about spliceosomal, and self-splicing introns, respectively.

  1. SR Eddy, "What is a hidden Markov model?" Nat. Biotechnol., 22, #10 (2004) 1315-6. [offcampus]
  2. LR Rabiner, "A Tutorial on Hidden Markov Models and Selected Application in Speech Recognition," Proceedings of the IEEE, v 77 #2,Feb 1989, 257-286.
  3. C Burge, S Karlin, "Prediction of complete gene structures in human genomic DNA." J. Mol. Biol., 268, #1 (1997) 78-94. [offcampus]
  4. M Burset, R Guigó, "Evaluation of gene structure prediction programs." Genomics, 34, #3 (1996) 353-67. [offcampus]
  5. JM Claverie, "Computational methods for the identification of genes in vertebrate genomic sequences." Hum. Mol. Genet., 6, #10 (1997) 1735-44. [offcampus]
  6. An extensive online bibliography
  7. ES Lander, LM Linton, B Birren, C Nusbaum, MC Zody, J Baldwin, K Devon, K Dewar, M Doyle, W FitzHugh, et 247 al., "Initial sequencing and analysis of the human genome." Nature, 409, #6822 (2001) 860-921. [offcampus]
  8. JC Venter, MD Adams, EW Myers, PW Li, RJ Mural, GG Sutton, HO Smith, M Yandell, CA Evans, RA Holt, et 264 al., "The sequence of the human genome." Science, 291, #5507 (2001) 1304-51. [offcampus]
  9. RJ Klein, Z Misulovin, SR Eddy, "Noncoding RNA genes identified in AT-rich hyperthermophiles." Proc. Natl. Acad. Sci. U.S.A., 99, #11 (2002) 7542-7. [offcampus]
  10. Sharp's Nobel address on discovery of introns.
  11. JP Staley, C Guthrie, "Mechanical devices of the spliceosome: motors, clocks, springs, and things." Cell, 92, #3 (1998) 315-26. [offcampus]
  12. DR Edgell, VR Chalamcharla, M Belfort, "Learning to live together: mutualism between self-splicing introns and their hosts." BMC Biol., 9, (2011) 22. [offcampus]

References -- RNA Structure, Alignment, & Search: Read #39, 43, 45, 47. Optional: Refs 34-37 are good surveys of recent surprising discoveries about the roles of non-coding RNA. Refs 51-53 might give you some picture of one nice biological example and how computational approaches are useful in this arena. Ref #54 and following describe our recent approaches to RNA motif discovery in bacteria and vertebrates.

  1. G Storz, "An expanding universe of noncoding RNAs." Science, 296, #5571 (2002) 1260-3. [offcampus]
  2. SR Eddy, "Computational genomics of noncoding RNA genes." Cell, 109, #2 (2002) 137-40. [offcampus]
  3. A Hüttenhofer, P Schattner, N Polacek, "Non-coding RNAs: hope or hype?" Trends Genet., 21, #5 (2005) 289-97. [offcampus]
  4. G Ruvkun, "The perfect storm of tiny RNAs." Nat. Med., 14, #10 (2008) 1041-5. [offcampus]
  5. J Gorodkin, IL Hofacker, E Torarinsson, Z Yao, JH Havgaard, WL Ruzzo, "De novo prediction of structured RNAs from genomic sequences." Trends Biotechnol., 28, #1 (2010) 9-19. [offcampus]
  6. SR Eddy, "How do RNA folding algorithms work?" Nat. Biotechnol., 22, #11 (2004) 1457-8. [offcampus]
  7. JS McCaskill, "The equilibrium partition function and base pair binding probabilities for RNA secondary structure." Biopolymers, 29, #6-7 (1990 May-Jun) 1105-19. [offcampus]
  8. RB Lyngsø, M Zuker, CN Pedersen, "Fast evaluation of internal loops in RNA secondary structure prediction." Bioinformatics, 15, #6 (1999) 440-5. [offcampus]
  9. PP Gardner, R Giegerich, "A comprehensive comparison of comparative RNA structure prediction approaches." BMC Bioinformatics, 5, (2004) 140. [offcampus]
  10. SR Eddy, R Durbin, "RNA sequence analysis using covariance models." Nucleic Acids Res., 22, #11 (1994) 2079-88. [offcampus]
  11. SR Eddy, "A memory-efficient dynamic programming algorithm for optimal alignment of a sequence to an RNA secondary structure." BMC Bioinformatics, 3, (2002) 18. [offcampus]
  12. S Griffiths-Jones, A Bateman, M Marshall, A Khanna, SR Eddy, "Rfam: an RNA family database." Nucleic Acids Res., 31, #1 (2003) 439-41. [offcampus]
  13. S Griffiths-Jones, S Moxon, M Marshall, A Khanna, SR Eddy, A Bateman, "Rfam: annotating non-coding RNAs in complete genomes." Nucleic Acids Res., 33, #Database issue (2005) D121-4. [offcampus]
  14. Z Weinberg, WL Ruzzo, "Faster Genome Annotation of Non-coding RNA Families Without Loss of Accuracy." Eighth Annual International Conference on Research in Computational Molecular Biology (RECOMB 2004) , pp 243-251, March 2004, San Diego, CA. Preprint.
  15. Z Weinberg, WL Ruzzo, "Exploiting conserved structure for faster annotation of non-coding RNAs without loss of accuracy." Bioinformatics, 20 Suppl 1, (2004) I334-I341. [offcampus]
  16. Z Weinberg, WL Ruzzo, "Sequence-based heuristics for faster annotation of non-coding RNA families." Bioinformatics, 22, #1 (2006) 35-9. [offcampus]
  17. M Mandal, M Lee, JE Barrick, Z Weinberg, GM Emilsson, WL Ruzzo, RR Breaker, "A glycine-dependent riboswitch that uses cooperative binding to control gene expression." Science, 306, #5694 (2004) 275-9. [offcampus]
  18. JE Barrick, N Sudarsan, Z Weinberg, WL Ruzzo, RR Breaker, "6S RNA is a widespread regulator of eubacterial RNA polymerase that resembles an open promoter." RNA, 11, #5 (2005) 774-84. [offcampus]
  19. AE Trotochaud, KM Wassarman, "A highly conserved 6S RNA structure is required for regulation of transcription." Nat. Struct. Mol. Biol., 12, #4 (2005) 313-9. [offcampus]
  20. DK Willkomm, J Minnerup, A Hüttenhofer, RK Hartmann, "Experimental RNomics in Aquifex aeolicus: identification of small non-coding RNAs and the putative 6S RNA homolog." Nucleic Acids Res., 33, #6 (2005) 1949-60. [offcampus]
  21. Z Yao, Z Weinberg, WL Ruzzo, "CMfinder--a covariance model based RNA motif finding algorithm." Bioinformatics, 22, #4 (2006) 445-52. [offcampus]
  22. Z Yao, J Barrick, Z Weinberg, S Neph, R Breaker, M Tompa, WL Ruzzo, "A computational pipeline for high- throughput discovery of cis-regulatory noncoding RNA in prokaryotes." PLoS Comput. Biol., 3, #7 (2007) e126. [offcampus]
  23. Z Weinberg, JE Barrick, Z Yao, A Roth, JN Kim, J Gore, JX Wang, ER Lee, KF Block, N Sudarsan, et 4 al., "Identification of 22 candidate structured RNAs in bacteria using the CMfinder comparative genomics pipeline." Nucleic Acids Res., 35, #14 (2007) 4809-19. [offcampus]
  24. EE Regulski, RH Moy, Z Weinberg, JE Barrick, Z Yao, WL Ruzzo, RR Breaker, "A widespread riboswitch candidate that controls bacterial genes involved in molybdenum cofactor and tungsten cofactor metabolism." Mol. Microbiol., 68, #4 (2008) 918-32. [offcampus]
  25. Z Weinberg, EE Regulski, MC Hammond, JE Barrick, Z Yao, WL Ruzzo, RR Breaker, "The aptamer core of SAM-IV riboswitches mimics the ligand-binding site of SAM-I riboswitches." RNA, 14, #5 (2008) 822-8. [offcampus]
  26. E Torarinsson, Z Yao, ED Wiklund, JB Bramsen, C Hansen, J Kjems, N Tommerup, WL Ruzzo, J Gorodkin, "Comparative genomics beyond sequence-based alignments: RNA structures in the ENCODE regions." Genome Res., 18, #2 (2008) 242-51. [offcampus]
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