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Section 1: Monday 2:15 - 3:15pm, students will give 15 ~ 20 min presentations of the papers (Bass 405). To sign up for presentations, see the spreadsheet.
Section 2: Monday 4:00 - 5:00pm, will have a discussion format. (Bass 405 or Bass 205)
Each section will include discussion of papers assigned (below). Students are expected to bring 1-2 paragraph summaries of each paper to the section (hard copy is preferred). The written assignment will be the same, and students will be graded on a combination of the written assignments and your participation in discussions.
MOOC Lectures (for class on March 2 and March 4):
X. Advice for Applying Machine Learning (Week 6)
X. Advice for Applying Machine Learning (Week 6)
10.1: https://www.youtube.com/watch?v=DYCv5e0Isow
10.2: https://www.youtube.com/watch?v=75PiDvoQc7o
10.3: https://www.youtube.com/watch?v=2bgDlLJtjoQ
10.4: https://www.youtube.com/watch?v=wfmmNmXqGrc
10.5: https://www.youtube.com/watch?v=pk8sz0akmck
10.6: https://www.youtube.com/watch?v=g4XluwGYPaA
10.7: https://www.youtube.com/watch?v=TxJe4xeDI7g
XI. Machine Learning System Design (Week 6)
XI. Machine Learning System Design (Week 6)
11.1: https://www.youtube.com/watch?v=E9Ki-sThq5E
11.2: https://www.youtube.com/watch?v=cSehNXLYU54
11.3: https://www.youtube.com/watch?v=Aikq-iPQtx0
11.4: https://www.youtube.com/watch?v=OEYvj3sW9t4
11.5: https://www.youtube.com/watch?v=eVA-n9V4fQ8
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
To sign up for presentations, click http://goo.gl/TmBfoz
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