Section Readings

Weekly Discussion Sections & Readings
Group 1: Friday 1:00 - 2:00 PM, BASS 405
Group 2: Monday 12:00 - 1:00 PM, BASS 405
 
The first discussion section will meet on 1/29/2016 (Group 1) and 2/1/2016 (Group 2).

Format
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 cbb752@gersteinlab.org BEFORE each section).
  • Students will give approx. 15 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

Session 1: Next-Gen Sequencing 
  • Metzker ML. "Sequencing technologies - the next generation” Nature Reviews Genetics. 11 (2010) 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 
  • T.F. Smith and M.S. Waterman. (1981) Identification of common molecular subsequences. Journal of Molecular Biology,147(1): 195-7. PMID: 7265238. PDF  
  • Nevan J. Krogan et al (2006) Global landscape of protein complexes in the yeast Saccharomyces cerevisiae Nature 440, 637-643 (30 March 2006) PDF 
  • Additional readings suggested by Professor Rinehart 

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 
  • 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



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Slides for the first TA section  8799k v. 1 Feb 17, 2016, 1:52 PM Xiu Huang