Seminar: Information processing in living systems – SS12

Lecturer: Dr. Jürgen Pahle

Schedule: Block seminar on 15th June 2012, from 14:30 (Building E1 3, room 528).
Registration: Please make an appointment with Dr. Pahle (pahle(-at-) to register for the seminar and agree on a topic.
Registration deadline: 20th April 2012
Write-up deadline: 6th July 2012

Credits: 7 ECTS points

The seminar is designed for bioinformatics and computer science students. Basic knowledge about information theory and modelling biochemical networks is helpful for a successful participation. The language of the seminar is English (presentation and write-up).

Requirements for successful participation (“Schein”)
Every participant will give a presentation of 30 to 45 min on one of the topics listed below. Participants who give presentations of very low quality will have to repeat their presentation to get a “Schein”.

Every participant has to submit a write-up on their topic three weeks after the presentations. The write-up should be at least 5 pages and submitted electronically as pdf-file.

Paper reading: Each participant has to be the “opponent” for at least two speakers, i.e., she/he has to read the related paper(s) in advance and prepare questions for the speaker.

Participants must present their slides to the seminar supervisor not later than two weeks before the block seminar.

One of the biggest challenges of living systems -be it single cells or whole organisms- is to sense their environment, process a multitude of inputs and, finally, decide how to (re-)act in a consistent and reliable way. This has to be achieved despite external and internal noise (e.g. fluctuations in molecule numbers), sometimes contradictory inputs and unreliable components. For instance, a variety of hormonal stimuli, changing concentrations of nutrients, electro-chemical signals and, of course, the changing internal state of the cells themselves (i.e. the number and localisation of all molecules etc. in the cell), all need to be followed and acted upon appropriately.

This illustrates that there is much biological computation involved, not only inter-cellularly, e.g. in neural systems, but also already on an intracellular biochemical level. This information processing can be quantified and studied using ideas from information theory, such as the Shannon entropy, mutual information and transfer entropy.

In this seminar we will cover the required basics of modelling biochemical networks, (stochastic) simulation and information theory. Each student is assigned a piece of primary literature to work on, discuss and present to the group.


  • Pahle, Green, Dixon and Kummer (2008) Information transfer in signaling pathways: A study using coupled simulated and experimental data. BMC Bioinformatics 9:139, doi:10.1186/1471-2105-9-139 (assigned to Thorsten Klingen)
  • Gourévitch and Eggermont (2007) Evaluating information transfer between auditory cortical neurons. J. Neurophysiol. 97:2533, doi:10.1152/jn.01106.2006 (assigned to Zeinab M.P.Aghdam)
  • Niven, Anderson and Laughlin (2007) Fly photoreceptors demonstrate energy-information trade-offs in neural coding. PLoS Biol. 5(4):e116, doi:10.1371/journal.pbio.0050116 (note: this doi link seems to be broken. In this case the article can also be found via the PLoS Biol. website) (assigned to Azim Dehghani Amirabad)
  • Staniek and Lehnertz (2008) Symbolic transfer entropy. PRL 100:158101, doi:10.1103/PhysRevLett.100.158101 (assigned to Ugur Kira)
  • Ziv, Nemenman and Wiggins (2007) Optimal signal processing in small stochastic biochemical networks. PLoS ONE 2(10):e1077, doi:10.1371/journal.pone.0001077 (assigned to Pramod Kaushik Mudrakarta)
  • Tkacik, Callan and Bialek (2008) Information flow and optimization in transcriptional regulation. PNAS 105(34):12265, doi:10.1073/pnas.0806077105 (assigned to Abirami Veluchamy)
  • Waltermann and Klipp (2011) Information theory based approaches to cellular signaling. BBA 1810:924, doi:10.1016/j.bbagen.2011.07.009 (assigned to Daria Gaidar)

Learning outcomes:
The students will learn ways of quantifying and studying information processing in living systems. This includes basics, such as stochastic modelling of biochemical networks and elements of information theory. They will also get to know current research in the field.