Stochastic models in biological systems

prof. dr hab. Jacek Miękisz, dr Anna Ochab-Marcinek (IChF PAN)

Tuesday 14.15-15.45 , room 403


1 March 2018

Olivier Rivoire (College de France, Paris)

Proteins in the light of evolution

Proteins illustrate at a molecular scale our difficulty to apprehend biological systems. They highlight, in particular, the limitations of classical biophysics approaches. Many proteins are indeed extremely well characterized, from their constituents to the principles that govern their interactions. Yet, we generally do not know how to relate the sequence of a protein to its physical and chemical properties. This difficulty may reflect an intrinsic complexity but, as I will explain, looking at the problem from an evolutionary perspective clearly points towards simplifying principles. I will present practical methods and theoretical models aimed at elucidating the nature and origin of this underlying simplicity.

27 February 2018

Olivier Rivoire (College de France, Paris)

Models of information processing in evolving populations

I will review mathematical models of evolutionary dynamics in which the adaptive value of different types of informations can be quantified. The models are inspired by information theory and, in some limits, correspond to known models of investment or stochastic control.

12 February 2018

Christian Maes (KU Leuven, Belgium)

Active in nonequilibrium

We discuss the new wave of models, called active particles, in nonequilibrium statistical mechanics. There are interesting relations with the telegraph equation and new views on pattern formation problems.


Thibaut Demaerel and Christian Maes, Active processes in one dimension

21 November 2017

Anna Ochab-Marcinek (IChF PAN)

Noise in gene expression: Cell division & Evolution of gene regulation

I am going to present the research topics that my research group works on:

1. Stochastic modeling of gene expression in dividing cells. I will present our recent models in which proteins are produced in random bursts, but the randomness of cell cycle duration and protein partitioning between daughter cells are the additional sources of noise. This addition allows us to correctly reproduce the noise vs. mean dependence of the experimental data and it provides more realistic estimates of the frequencies and sizes of protein bursts.

2. The role of gene expression noise in evolution of gene regulation. I am going to present the outline of the research project that I have just started.

14 November 2017

Jacek Miękisz (IMPAN and MIMUW)

Time delays in gene expression and evolutionary games

I begin with a short introduction to Simons Semester on Mathematical Biology in Banach Center,  December 2017 - March 2018

Then I introduce some particular mathematical models of micro and macro biology: Markov jump processes which describe gene expression and regulation in living cells and Markov chains in evolutionary games (we do not assume any knowlege of biology and game theory). I outline main goals and open problems. We will discuss possible effects that stochasticity and time delays may have on the behavior of deterministic dynamical systems.

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