Physics 380, 2011: Information Processing in Biology

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Back to Physics 380, 2011: Information Processing in Biology.


  • The class is over. Thanks for attending! Ilya 18:08, 6 December 2011 (UTC)
  • All past-due homeworks are due no later than 5pm of Dec 12. I will grade them and issue course grades on Dec 13 in the morning.
  • Study sessions schedule for the end of the semester:
    • Tuesday, Nov 22, 6pm
    • Tuesday, Nov 29, 6pm
    • Tuesday, Nov 6, 6pm
    • Thursday, Nov 8, 10 am (class time),
    • Monday, Nov 12, 9-12 am (my office).
  • I am slowly catching up with lecture notes. Lecture 14 has been added. Ilya 23:37, 14 November 2011 (UTC)
  • I am slowly catching up with lecture notes. Lecture 13 has been added. 13:16, 3 November 2011 (UTC)
  • Please make sure you submit your homework assignments on time. Ilya 13:16, 3 November 2011 (UTC)
    • Nov 4 -- the last day to submit homeworks 1-6.
    • Nov 18 -- the last day to submit 7-8.
  • The syllabus has been slightly updated for the upcoming lectures. Ilya 00:17, 25 October 2011 (UTC)
  • The class on 10/25 and the study session will be conducted by Martin Tchernookov. Ilya 00:17, 25 October 2011 (UTC)
  • The class on 9/29 and the study session on 9/27 will be conducted by Martin Tchernookov. Ilya 13:53, 27 September 2011 (UTC)
  • Lecture notes have been cleaned up, and references have been added. Ilya 13:47, 27 September 2011 (UTC)
  • Syllabus has been updated -- blocks 2 and 3 have been re-ordered. Ilya 13:17, 27 September 2011 (UTC)
  • Reading assignments for the first block have been posted. Ilya 13:17, 27 September 2011 (UTC)
  • Note that the classes on 9/13 and 9/15 will be conducted by Martin Tchernookov, and there will be no discussion session on 9/13. Ilya 20:55, 12 September 2011 (UTC)
  • The study session is in room N215. Ilya 03:19, 4 September 2011 (UTC)
  • Evening study session is at 6pm on Tuesdays. Ilya 13:41, 1 September 2011 (UTC)
  • Welcome to the class!


Lecture Notes

Homework assignments

Original Literature for Presentation in Class

A large part of the class grade will be determined by your in-class presentation of a recent research paper. Papers will be divided into four blocks, just like the whole class: Noise, information, dynamics, and adaptation/learning. In your presentations, aim for half an hour talk. Try to structure your presentations the following way:

  1. What is the question being asked?
  2. What are the findings of the authors?
  3. Which experimental or computational tools (whichever applicable) they use in their work?
  4. What in this findings is unique to the studied biological system, and what should be general?

Working individually, please select one paper from this list and be ready to present it during the identified week. Selections are on First Come - First Served basis.

  • Stochastic effects and their propagation. I need two people will present during the weeks of Oct 10 and 17. One person should select one of the first three papers, and the other should select one of the last two.
  1. Elowitz et al., 2002 -- this paper measures the effect of molecule noise on the single cell level
  2. Blake et al., 2003 -- noise in eukaryotic transcription is investigated
  3. Raser and O'Shea, 2004 -- measuring noise in yeast transcription: Reiser, October 20.
  4. Pedraza and van Oudenaarden, 2005 -- a study in noise propagation in transcriptional networks: Cheng, October 13.
  5. Cagatay et al., 2009 -- this papers analyses the phenomenon of competence in B. subtilis to conclude that large noise if functionally important
  • Information theoretic characterization of biological signaling. I need two people will present on Oct 27 and Nov 3. One person should select from the first two papers, and the other from the remaining two
  1. Strong et al., 1998 -- the authors calculate the amount of information transmitted by the fly motion sensitive neuron to the rest of the fly brain: Kamili
  2. Cheong et al., 2011 -- it took thirteen years to do a similar calculation for a molecular signaling pathway
  3. Andrews and Iglesias, 2007 -- in this paper, the authors study chemotaxis by a slime mold cell from the information-theoretic perspective
  4. Vergassola et al, 2007 -- one can find the source of smell by choosing steps that maximize the information about its location: Botezat
  • Dynamical information processing and dealing with noise. Please select one of the first three papers, and one of the second three. One presentation should be Nov 22, and the other Nov 29.
  1. Cagatay et al., 2009 -- this papers builds a (noisy) dynamical systems model of B. subtilis competence: Leung, Nov 22
  2. Walczak et al., 2010 -- these authors analyze how noise can be suppressed in development by averaging over multiple pathways, through which information is sent
  3. Lahav et al., 2004 -- to fight noise, biological systems may choose to communicate in a digital fashion
  4. Gardner et al., 2000 -- a bistable toggle switch has been constructed inside the E. coli
  5. Markevich et al., 2004 -- bistability can be achieved without obvious positive feedback
  6. Sprinzak et al., 2010 -- development, such as patterning an eye, also involves multistability, Gershon, Nov 29
  • Adaptation and learning. I am only giving three papers here. Each of the remaining three presenters should choose one.
  1. Gallistlel et al., 2001 -- this paper argues that a foraging rat learns (i.e., adapts to) optimally from its environment, Hobson, Nov 29
  2. Brenner et al., 2000 -- this neural system is capable of changing its gain: Dec 1, Zhang
  3. Fairhall et al., 2001 -- this same neural system, as it turns out, is capable of adjusting its response time: Dec 6, Owens


The list is far from being complete now. Stay tuned.


  1. R Phillips, J Kondev, J Theriot. Physical Biology of the Cell (Garland Science, 2008)
    • Sizing up E. coli. PDF
  2. CM Grinstead and JL Snell, Introduction to Probability.
  3. W Bialek, Biophysics: Searching for Principles (2011).
  4. For information about Wiener processes and diffusion, a good source is: Wiener Process article in Wikipedia.
  5. The most standard textbook on information theory is: T Cover and J Thomas, Elements of Information Theory, 2nd ed (Wiley Interscience, 2006).

Sensory Ecology and Corresponding Evolutionary Adaptations

  1. T Cronin, N Shashar, R Caldwell. Polarization vision and its role in biological signaling. Integrative and Comparative Biology 43(4):549-558, 2003. PDF.
  2. D Stavenga, Visual acuity of fly photoreceptors in natural conditions--dependence on UV sensitizing pigment and light-controlling pupil. J Exp Biol 207 (Pt 10) pp. 1703-13, 2004. PDF.

Transcriptional regulation

  1. O Berg and P von Hippel. Selection of DNA binding sites by regulatory proteins. Statistical-mechanical theory and application to operators and promoters. J Mol Biol. 193(4):723-50, 1987. PDF.
  2. O Berg et al. Diffusion-driven mechanisms of protein translocation on nucleic acids. 1. Models and theory. Biochemistry 20(24):6929-48, 1981. PDF.
  3. C Guet, M Elowitz, W Hsing, S Leibler. Combinatorial synthesis of genetic networks. Science 296:1466, 2002. PDF.
  4. M Slutsky and L Mirny. Kinetics of protein-DNA interaction: facilitated target location in sequence-dependent potential. Biophysical J 87(6):4021-35, 2004. PDF.
  5. E Ozbudak, M Thattai, H Lim, B Shraiman, A van Oudenaarden. Multistability in the lactose utilization network of Escherichia coli. Nature 427: 737, 2004. PDF.
  6. D Dreisigmeyer, J Stajic, I Nemenman, W Hlavacek, and M Wall. Determinants of bistability in induction of the Escherichia coli lac operon. IET Syst Biol 2:293-303, 2008. PDF.

Signal Processing in Vision

  1. P Detwiler et al. Engineering aspects of enzymatic signal transduction: Photoreceptors in the retina. Biophys. J., 79:2801-2817, 2000. PDF.
  2. A Pumir et al. Systems analysis of the single photon response in invertebrate photoreceptors. Proc Natl Acad Sci USA 105 (30) pp. 10354-9, 2008. PDF.
  3. F Rieke and D Baylor. Single photon detection by rod cells of the retina. Rev Mod Phys 70, 1027-1036, 1998. PDF.
  4. T Doan, A Mendez, P Detwiler, J Chen, F Rieke. Multiple phosphorylation sites confer reproducibility of the rod's single-photon responses. Science 313, 530-533, 2006. PDF.

Bacterial chemotaxis

  1. J Adler. Chemotaxis in bacteria. Annu Rev Biochem 44 pp. 341-56, 1975. PDF
  2. H Berg and D Brown. Chemotaxis in Escherichia coli analysed by three-dimensional tracking. Nature 239 (5374) pp. 500-4, 1972. PDF.
  3. E Budrene and H Berg. Dynamics of formation of symmetrical patterns by chemotactic bacteria. Nature 376 (6535) pp. 49-53, 1995. PDF
  4. E Budrene and H Berg. Complex patterns formed by motile cells of Escherichia coli. Nature 349 (6310) pp. 630-3, 1991. PDF
  5. E Purcell. Life at low Reynolds number. Am J Phys 45 (1) pp. 3-11, 1977. PDF
  6. H Berg. Motile behavior of bacteria. Phys Today 53 (1) pp. 24-29, 2000. PDF
  7. C Rao and A Arkin. Design and diversity in bacterial chemotaxis: a comparative study in Escherichia coli and Bacillus subtilis. PLoS Biol 2 (2) pp. E49, 2004. PDF
  8. C Rao et al. The three adaptation systems of Bacillus subtilis chemotaxis. Trends Microbio l16 (10) pp. 480-7, 2008. PDF.
  9. A Celani and M Vergassola. Bacterial strategies for chemotaxis response. Proc Natl Acad Sci USA107, 1391-6, 2010. PDF.

Eukaryotic chemotaxis

  1. J Franca-Koh et al. Navigating signaling networks: chemotaxis in Dictyostelium discoideum. Curr Opin Genet Dev 16 (4) pp. 333-8, 2006. PDF.
  2. W-J Rappel et al. Establishing direction during chemotaxis in eukaryotic cells. Biophysical Journal 83 (3) pp. 1361-7, 2002. PDF.

Random walks

  1. G Bel, B Munsky, and I Nemenman. The simplicity of completion time distributions for common complex biochemical processes. Physical Biology 7 016003, 2010. PDF.

Information theory

  1. J Ziv and A Lempel. A Universal Algorithm for Sequential Data Compression. IEEE Trans. Inf. Thy 3 (23) 337, 1977. PDF.
  2. N Tishby, F Pereira, and W Bialek. The information bottleneck method. arXiv:physics/0004057v1, 2000. PDF.
  3. E Ziv, I Nemenman, and C Wiggins. Optimal signal processing in small stochastic biochemical networks. PLoS ONE 2: e1077, 2007. PDF.
  4. S Strong, R Koberle, R de Ruyter van Steveninck, and W Bialek. Entropy and information in neural spike trains. Phys Rev Lett 80:197–200, 1998. PDF.
  5. R Cheong, A Rhee, CJ Wang, I Nemenman, and A Levchenko. Information Transduction Capacity of Noisy Biochemical Signaling Networks. Science doi:10.1126/science.1204553, 2011. PDF.

Noise in biochemistry, population biology, and neuroscience

  1. S Luria and M Delbruck. Mutations of bacteria from virus sensitivity to virus resistance. Genetics 28, 491-511, 1943. PDF.
  2. E Schneidman, B Freedman, and I Segev. Ion channel stochasticity may be critical in determining the reliability and precision of spike timing. Neural Comp. 10, p.1679-1704, 1998. PDF.
  3. T Kepler and T Elston. Stochasticity in transcriptional regulation: Origins, consequences, and mathematical representations. Biophys J. 81, 3116-3136, 2001. PDF.
  4. M Elowitz, A Levine, E Siggia & P Swain. Stochastic gene expression in a single cell. Science 207, 1183, 2002. PDF.
  5. W Blake, M Kaern, C Cantor, and J Collins. Noise in eukaryotic gene expression. Nature 422, 633-637, 2003. PDF.
  6. J Raser and E O’Shea. Control of stochasticity in eukaryotic gene expression. Science 304, 1811-1814, 2004. PDF.
  7. G Lahav. et al. Dynamics of the p53-Mdm2 feedback loop in individual cells. Nat Genet 36, 147–150, 2004. PDF.
  8. J Paulsson. Summing up the noise in gene networks. Nature 427, 415, 2004. PDF, Supplement.
  9. J Pedraza and A van Oudenaarden. Noise propagation in gene networks, Science 307, 1965-1969, 2005. PDF.
  10. N Rosenfeld, J Young, U Alon, P Swain, M Elowitz. Gene Regulation at the Single-Cell Level. Science 307, 1962, 2005. PDF.
  11. B Averbeck et al. Neural correlations, population coding and computation. Nat Rev Neurosci 7, 358-66, 2006. PDF.
  12. D Gillespie. Stochastic Simulation of Chemical Kinetics. Ann Rev Phys Chem 58, 35-55, 2007. PDF.
  13. T Cağatay et al. Architecture-dependent noise discriminates functionally analogous differentiation circuits. Cell 139:512-22, 2009. PDF, supplement.
  14. A Walczak, G Tkacik, and W Bialek. Optimizing information flow in small genetic networks. II. Feed-forward interactions. Phys Rev E 81, 041905, 2010. PDF.

Memory in noisy environments

  1. T Gardner et al. Construction of a genetic toggle switch in Escherichia coli. Nature 403: 339-42, 2000. PDF
  2. W Bialek. Stability and noise in biochemical switches. In Todd K. Leen, Thomas G. Dietterich, and Volker Tresp, editors, Advances in Neural Information Processing Systems 13, pages 103-109. MIT Press, 2001. PDF
  3. E Aurell and K Sneppen. Epigenetics as a first exit problem. Phys Rev Lett 88, 048101, 2002. PDF.
  4. E Korobkova, T Emonet, JMG Vilar, TS Shimizu, and P Cluzel. From molecular noise to behavioural variability in a single bacterium. Nature, 438:574-578, 2004. PDF.
  5. N Balaban, J Merrin, R Chait, L Kowalik, S Leibler. Bacterial persistence as a phenotypic switch. Science 305:1622, 2004. PDF.
  6. Y Tu and G Grinstein. How white noise generates power-law switching in bacterial flagellar motors. Phys Rev Lett, 2005. PDF.
  7. E Kussell and S Leibler. Phenotypic diversity, population growth, and information in fluctuating environments. Science 309:2075–2078. 2005. PDF.
  8. D Sprinzak et al. Cis-interactions between Notch and Delta generate mutually exclusive signalling states. Nature 465, 86–90, 2010. PDF.


  1. N Barkai and S Leibler. Robustness in simple biochemical networks. Nature 387, 913–917, 1997. PDF.
  2. U Alon, M Surette, N Barkai, and S Leibler. Robustness in bacterial chemotaxis. Nature 397, 168–171, 1999. PDF.
  3. N Brenner et al. Adaptive rescaling maximizes information transmission. Neuron 26, 695-702. PDF.
  4. P Cluzel, M Surette, and S Leibler. An ultrasensitive bacterial motor revealed by monitoring signaling proteins in single cells. Science, 287:1652-1655, 2000. PDF.
  5. B Andrews et al. Optimal noise filtering in the chemotactic response of Escherichia coli. PLoS Comput Biol 2, e154, 2006. PDF.
  6. T Sharpee et al. Adaptive filtering enhances information transmission in visual cortex. Nature 439, 936-42, 2006. PDF.
  7. A Fairhall et al. Efficiency and ambiguity in an adaptive neural code. Nature 412, 787-92, 2001. PDF.
  8. I Nemenman et al. Neural coding of natural stimuli: information at sub-millisecond resolution. PLoS Comput Biol 4, e1000025, 2008. PDF.
  9. T Friedlander and N Brenner. Adaptive response by state-dependent inactivation. Proc Natl Acad Sci USA 106, 22558-63, 2009. PDF.
  10. W Ma et al. Defining network topologies that can achieve biochemical adaptation. Cell 138, 760-73, 2009. PDF.


  1. A Eldar, D Rosin, B-Z Shilo, and N Barkai. Self-Enhanced Ligand Degradation Underlies Robustness of Morphogen Gradients. Developmental Cell, Vol. 5, 635–646, 2003. PDF.
  2. T Gregor, W Bialek, R de Ruyter van Steveninc, D Tank, and E Wieschaus. Diffusion and scaling during early embryonic pattern formation. PNAS 102:18403, 2005. PDF.
  3. T Doan, A Mendez, P Detwiler, J Chen, F Rieke. Multiple phosphorylation sites confer reproducibility of the Rod's single-photon responses. Science 313, 530-3, 2006. PDF.
  4. A Lander et al. The measure of success: constraints, objectives, and tradeoffs in morphogen-mediated patterning. Cold Spring Harb Perspect Biol 1, a002022, 2009. PDF


  1. CR Gallistel et al. The rat approximates an ideal detector of changes in rates of reward: implications for the law of effect. J Exp Psychol Anim Behav Process 27, 354-72, 2001. PDF.
  2. CR Gallistel et al. The learning curve: implications of a quantitative analysis. Proc Natl Acad Sci USA 101, 13124-31, 2004. PDF.
  3. B Andrews and P Iglesias. An information-theoretic characterization of the optimal gradient sensing response of cells. PLoS Comput Biol 3, e153, 2007. PDF.
  4. M Vergassola et al. 'Infotaxis' as a strategy for searching without gradients. Nature 445, 406-9, 2007. PDF.

Eukaryotic signaling

  1. C-Y Huang and J Ferrell. Ultrasensitivity in the mitogen-activated protein kinase cascade. Proc Natl Acad Sci USA 93:10078, 1996. PDF.
  2. N Markevich et al. Signaling switches and bistability arising from multisite phosphorylation in protein kinase cascades. J Cell Biol 164:353-9, 2004. PDF.
  3. C Gomez-Uribe, G Verghese, and L Mirny. Operating regimes of signaling cycles: statics, dynamics, and noise filtering. PLoS Comput Biol 3:e246, 2007. PDF.