Section Readings

Weekly Discussion Sections & Readings
Mondays, Bass 405 2:20 pm - 3:20 pm; or 6:00 - 7:00 pm


The standard discussion section involves student presentations on 1 or 2 papers. Some discussion sections will involve hands-on skill-building demos taught by the teaching fellows, such as the use of R, High Performance Computing, and GitHub. 

The exact format will be determined based on the size of the class. However, tentatively, we require the following
  • Students are expected to bring approx. a half page (2-3 paragraph) summaries of each paper to the section. (we will collect a hard copy during each session, but if you'd like to save some trees, we will accept electronic submission. Please submit PDF to cbb752 (at) BEFORE each section).
  • Students will give approx. 20 min presentations about each paper.
  • Students will be graded on a combination of the written summary, presentation, and participation in discussions.

Section Readings
Reading assignments for discussion sessions are listed below.

Session 0: Introductory Matters; Monday, 1/22/18, Bass 405 2:30 pm - 3:30 pm; 5:00 - 6:00 pm
  • No required reading
  • Come to either the 2:30 or 5:00 pm session depending on what is most convenient for you
  • These may not be the semester-long days and times
  • Email the TAs at if you cannot attend either session

Session 1: Next-Gen Sequencing; Monday, 1/29/18, Bass 405 2:20 pm - 3:20 pm; 6:00 - 7:00 pm
  • Goodwin S. et al. "Coming of age: ten years of next-generation sequencing technologies" Nature Reviews Genetics. 17 (2016) PDF
  • Wheeler DA et al. "The complete genome of an individual by massively parallel DNA sequencing,” Nature. 452:872-876 (2008) PDF 

Session 2: Proteomics/Sequence Alignment; 2/5/18
  • A draft map of the human proteome. Nature 509,575–581 (29 May 2014) PDF 
  • Mass-spectrometry-based draft of the human proteome. Nature 509, 582–587 (29 May 2014 ) PDF 

Session 3: Midterm Review: Needleman-Wunsch Alignment; 2/12/18

Session 4: Sequence Alignment/Machine learning; 2/19/18
  • Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. (1990) Basic local alignment search tool. Journal of Molecular Biology, 215(3):403-10. PMID: 2231712. PDF 
  • T.F. Smith and M.S. Waterman. (1981) Identification of common molecular subsequences. Journal of Molecular Biology,147(1): 195-7. PMID: 7265238. PDF  
  • Yip, KY, Cheng, C, Gerstein, M (2013). Machine learning and genome annotation: a match meant to be?. Genome Biol., 14, 5:205. PDF 

Session 5: Hands-On Demo on Alignment and Variant Calling; 2/26/18

Session 6: Bioinformatics for Next-Gen Sequencing; 3/5/18
  • Rozowsky, J, Euskirchen, G, Auerbach, RK, Zhang, ZD, Gibson, T, Bjornson, R, Carriero, N, Snyder, M, Gerstein, MB (2009). PeakSeq enables systematic scoring of ChIP-seq experiments relative to controls. Nat. Biotechnol., 27, 1:66-75 PDF 
  • Cooper, GM, Shendure, J (2011). Needles in stacks of needles: finding disease-causal variants in a wealth of genomic data. Nat. Rev. Genet., 12, 9:628-40 PDF

Session 7: Final Project Planning; 3/26/18

Session 8: Networks; 4/2/18
  • Ekman D, Light S, Björklund AK, Elofsson A. (2006) What properties characterize the hub proteins of the protein-protein interaction network of Saccharomyces cerevisiae? Genome Biol. 2006;7(6):R45. PDF 
  • Barabási, AL, Oltvai, ZN (2004). Network biology: understanding the cell's functional organization. Nat. Rev. Genet., 5, 2:101-13. PDF 

Session 9: Workshop on Detecting Cancer Driver Genes; 4/09/18

Session 10: Protein Simulation; 4/16/18
  • Zhou, AQ, O'Hern, CS, Regan, L (2011). Revisiting the Ramachandran plot from a new angle. Protein Sci., 20, 7:1166-71 PDF 
  • Dill KA, Ozkan SB, Shell MS, Weikl TR. (2008) The Protein Folding Problem.Annu Rev Biophys,9, 37:289-316. PMID: 2443096.PDF 
  • Bowman GR, Beauchamp KA, Boxer G, Pande VS. “Progress and challenges in the automated construction of Markov state models for full protein systems,” J. Chem. Phys. 131 (2009) 124101 PDF

Session 11: Final Project Presentations; 4/23/18

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