Section Readings

Weekly Discussion Sections & Readings
Group 1: Friday 1:00pm - 2:00pm
Group 2: Tuesday 6:00pm - 7:00pm

In each section, we will have a discussion of two papers assigned below.

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 BEFORE each section).
  • Students will give approx. 20 min presentations about each paper. (To sign up for presentations, see the spreadsheet below)
  • Students will be graded on a combination of the written summary, presentation, and participation in discussions.

Section Readings

Introduction to Personalized Medicine:

Session 1: Next-Gen Sequencing 
  • 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 

Session 3: Sequence Alignment/Machine learning 
  • 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 4: Bioinformatics for Next-Gen Sequencing 
  • 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 5: Networks 
  • 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 6: Immunological Modeling/Semantic Web 
  • Perelson AS. Modelling viral and immune system dynamics. Nat Rev Immunol. 2002 Jan;2(1):28-36. PDF 
  • Antezana E, Egaña M, Blondé W, Illarramendi A, Bilbao I, De Baets B, Stevens R, Mironov V, Kuiper M. (2009) The Cell Cycle Ontology: an application ontology for the representation and integrated analysis of the cell cycle process. Genome Biol. 2009;10(5):R58. Epub 2009 May 29. PDF 

Session 7: Protein Simulation 1 
  • Martin Karplus and J. Andrew McCammon. (2002) Molecular dynamics simulations of biomolecules. Nature Structural Biology,9, 646-52. PMID: 12198485.PDF 
  • Zhou, AQ, O'Hern, CS, Regan, L (2011). Revisiting the Ramachandran plot from a new angle. Protein Sci., 20, 7:1166-71 PDF 

Session 8: Protein Simulation 2 
  • 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 9: CRISPR off target prediction
  • Shengdar Q. Tsai and J. Keith Joung (2016) Defining and improving the genomewide specificities of CRISPR–Cas9 nucleases PDF 
  • Alexendar R Perez et al. (2017) GuideScan software for improved single and paired CRISPR guide RNA design PDF

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