Current Topics in Computational Biology, Fall 2015

Instructor: Tim Lezon (; 9048 BST3; 412.383.8042)

Time: Mondays 12:30-13:25

Place: 3073 BST3 (3rd floor classroom)

Students may choose to present one of the following pre-approved papers, or may select another paper and submit it to the instructor for approval two weeks prior to the presentation date.

Tips for selecting your own paper

If you want to select your own paper to present, that's fine. Here are some things to keep in mind:

Pre-selected Papers

  1. Zhou Y, Wong C-O, Cho K, van der Hoeven D, Liang H, Thakur DP, Luo J, Babic M, Zinsmaier KE, Zhu MX, Hu H, Venkatachalam K and Hancock JF. Membrane potential modulates plasma membrane phospholipid dynamics and K-Ras signaling. Science 349:873-876 (2015).
  2. MacCallum JL, Perez A and Dill KA. Determining protein structures by combining semireliable data with atomistic physical models by Bayesian inference. Proc Natl Acad Sci USA 112:6985-6990 (2015).
  3. Bakan A, Kapralov AA, Bayir H, Kagan VE and Bahar I. Inhibition of Peroxidase Activity of Cytochrome c: De Novo Compound Discovery and Validation. Mol Pharmacol 88:421-427 (2015).
  4. Kellogg RA and Tay S. Noise facilitates transcriptional control under dynamic inputs. Cell 160:381-392 (2015).
  5. Moreno-Gamez S, Hill AL, Rosenbloom DIS, Petrov DA, Nowak MA and Pennings PS. Imperfect drug penetration leads to spatial monotherapy and rapid evolution of multidrug resistance. Proc Natl Acad Sci USA 112:E2874 (2015).
  6. Zañudo JGT and Albert R. Cell Fate Reprogramming by Control of Intracellular Network Dynamics. PLoS Comp Biol 11:e1004193 (2015).
  7. Ghiassian SD, Menche J and Barabási A-L. A DIseAse MOdule Detection (DIAMOnD) Algorithm Derived from a Systematic Analysis of Connectivity Patterns of Disease Proteins in the Human Interactome. PLoS Comp Biol 11:e1004120 (2015).
  8. Zhang J and Yang J-R. Determinants of the rate of protein sequence evolution. Nat Rev Genet 16:409-420 (2015).
  9. Stratton M, Lee I-H, Bhattacharyya M, Christensen SM, Chao LH, Schulman H, Groves JT and Kuriyan J. Activation-triggered subunit exchange between CaMKII holoenzymes facilitates the spread of kinase activity. eLife 3:e01610 (2014)..
  10. Kohloff KJ, Shukla D, Lawrenz M, Bowman GR, Konerding DE, Belov D, Altman RB and Pande VS. Cloud-based simulations on Google Exacycle reveal ligand modulation of GPCR activation pathways. Nat Chem 6:15-21 (2014).
  11. Leder K, Pitter K, Laplant Q, Hambardzumyan D, Ross BD, Chan TA, Holland EC and Michor F. Mathematical modeling of PDGF-driven glioblastoma reveals optimized radiation dosing schedules. Cell 156:603-616 (2014).
  12. Regot S, Hughey JJ, Bajar BT, Carrasco S and Covert MW. High-sensitivity measurements of multiple kinase activities in live single cells. Cell 157:1724-1734 (2014).
  13. Zhang J, Tian X-J, Zhang H, Teng Y, Li R, Bai F, Elankumaran S and Xing J. TGF-β induced epithelial-to-mesenchymal transition proceeds through stepwise activation of multiple feedback loops. Science Signaling 7:ra91 (2014).
  14. Selimkhanov J, Taylor B, Yao J, Pilko A, Albeck J, Hoffmann A, Tsimring L and Wollman R. Accurate information transmission through dynamic biochemical signaling networks. Science 346:1370-1373 (2014).
  15. Li Y, Calvo SE, Gutman R, Liu JS and Mootha VK. Expansion of Biological Pathways Based on Evolutionary Inference. Cell 158:213 (2014).
  16. Lee REC, Walker SR, Savery K, Frank DA and Gaudet S. Fold change of nuclear NF-κB determines TNF-induced transcription in single cells. Mol Cell 53:867-879 (2014).
  17. Tönsing C, Timmer J and Kreutz C. Cause and cure of sloppiness in ordinary differential equation models. Phys Rev E 90:023303 (2014).
  18. Sherwood RI, Hashimoto T, O'Donnell CW, Lewis S, Barkal AA, van Hoff JP, Karun V, Jaakkola T and Gifford DK. Discovery of directional and nondirectional pioneer transcription factors by modeling DNase profile magnitude and shape. Nat Biotechnol 32:171-178 (2014).
  19. Brewster RC, Weinert FM, Garcia HG, Song D, Rydenfelt M and Phillips R. The transcription factor titration effect dictates level of gene expression. Cell 156:1312-1323 (2014).
  20. Ramsey JD, Sanchez-Romero R and Glymour C. Non-Gaussian methods and high-pass filters in the estimation of effective connections. Neuroimage 84:986-1006 (2014).
  21. Savir Y and Tlusty T. The Ribosome as an Optimal Decoder: A Lesson in Molecular Recognition. Cell 153:471-479 (2013).
  22. Toettcher JE, Weiner OD and Lim WA. Using Optogenetics to Interrogate the Dynamic Control of Signal Transmission by the Ras/Erk Module Cell 155:1422-1434 (2013).
  23. Dror RO, Green HF, Valant C, Borhani DW, Valcourt JR, Pan AC, Arlow DH, Canals M, Lane JR, Rahmani R, Baell JB, Sexton PM, Christopoulos A and Shaw DE. Structural basis for modulation of a G-protein-coupled receptor by allosteric drugs. Nature 503:295-300 (2013).
  24. Gumbart JC, Teo I, Roux B and Schulten K. Reconciling the roles of kinetic and thermodynamic factors in membrane-protein insertion. J Am Chem Soc 135:2291-2297 (2013).
  25. Ziervogel BK and Roux B. The binding of antibiotics in OmpF porin. Structure 21:76-87 (2013).
  26. Tian X-J, Zhang H and Xing J. Coupled Reversible and Irreversible Bistable Switches Underlying TGFβ-induced Epithelial to Mesenchymal Transition. Biophys J 105:1079-1089 (2013).
  27. Albeck JG, Mills GB and Brugge JS. Frequency-modulated pulses of ERK activity transmit quantitative proliferation signals. Mol Cell 49:249-261 (2013).
  28. Martins BMC and Swain PS. Ultrasensitivity in phosphorylation-dephosphorylation cycles with little substrate. PLoS Comp Biol 9:e1003175 (2013).
  29. Zhang W, Ota T, Shridhar V, Chien J, Wu B and Kuang R.  Network-based survival analysis reveals subnetwork signatures for predicting outcomes of ovarian cancer treatment. PLoS Comp Biol 8:e1002975 (2013).
  30. Paris M, Kaplan T, Li XY, Villalta JE, Lott SE and Eisen MB. Extensive divergence of transcription factor binding in Drosophila embryos with highly conserved gene expression. PLoS Genet 9:e1003748 (2013).
  31. Morris A Beck M, Schloss PD, Campbell TB, Crothers K, Curtis JL, Flores SC, Fontenot AP, Ghedin E, Huang L, Jablonski K, Kleerup E, Lynch SV, Sodergren E, Twigg H, Young VB, Bassis CM, Venkataraman A, Schmidt TM an dWeinstock GM. Comparison of the respiratory microbiome in healthy nonsmokers and smokers. Am J Respir Crit Care Med 187:1067-1075 (2013).
  32. Wen X, Rangarajan G and Ding M. Is Granger causality a viable technique for analyzing fMRI data? PLoS One 8:e67428 (2013).
  33. Seth AK, Chorley P and Barnett LC. Granger causality analysis of fMRI BOLD signals is invariant to hemodynamic convolution but not downsampling. Neuroimage 65:540-555 (2013).
  34. Shan J, Schwartz RE, Ross NT, Logan DJ, Thomas D, Duncan SA, North TE, Goessling W, Carpenter AE and Bhatia SN. Identification of small molecules for human hepatocyte expansion and iPS differentiation. Nat Chem Biol 9:514-520 (2013).
  35. Koga N, Tatsumi-Koga R, Liu G, Xiao R, Acton TB, Montelione GT and Baker D. Principles for designing ideal protein structures. Nature 491:222-227 (2012).
  36. Ballester PJ and Mitchell JBO. A machine learning approach to predicting protein-ligand binding affinity with applications to molecular docking. Bioinformatics 26:1169-1175 (2010).