HuGeF, Via Nizza 52, Old Building, First floor, aula affrescata
Abstract: In mathematical models of subdivided populations (or metapopulations) migration acts together with selection and genetic drift to determine their evolution. In order to study the coupled dynamics of these populations, I will develop a self-consistent mean-field-like method that hinges on the presence of a separation of time scales between local and global dynamics and catches the effects of migration on relevant non-equilibrium properties, such as the mean fixation time. As an result, I will show that when the evolution strongly favors coexistence of species (e.g., balancing selection), the mean fixation time develops an unexpected minimum as a function of the migration rate. I will also discuss possible generalizations of the method to include sparseness effects on random graphs.
Marcin J. Skwark (The Finnish Centre of Excellence in Computational Inference)
HUGEF, old building 1st floor "Aula Affrescata"
Recent developments in co-evolution based contact prediction have been recently widely adopted by the structure prediction community, as evidenced in CASP11, a recently finished commnity-wide experiment in blind protein structure prediction.. According to organisers’ opinion, contact prediction was one of the “winners” of CASP this year. In this talk I will present how did the field of contact prediction progress recently and how are the inferred couplings applied to solving problems in biological settings. This talk will particularly focus on my contact-driven CASP method “my protein&me”, which ranked as 4th most group world-wide and was claimed as one of more unexpected developments in this years’ experiment. I will also discuss several success stories for contact prediction, in which successful contact inference allowed for discovering structural information that has not been attainable by other means. Finally, the talk will discuss the potential impact of introducing additional biological information in the inference process and prospective ways of increasing the applicability of these methods.
Sala Affrescata, HuGeF, Molecular Biology Center (MBC), Via Nizza 52
The problem of error correction for Gallager's low-density parity-check codes is notoriously equivalent to that of computing marginal Boltzmann probabilities for an Ising-like model with multispin interactions in a non-uniform magnetic field. Since the graph of interactions is locally a tree, the solution is very well approximated by a generalized mean-field (Bethe--Peierls) approximation. Belief propagation (BP) and similar iterative algorithms are an efficient way to perform the calculation, but they sometimes fail to converge, or converge to non-codewords, giving rise to a non-negligible residual error probability (error floor). On the other hand, provably-convergent algorithms are far too complex to be implemented in a real decoder. In this work we consider the application of the probability-damping technique, which can be regarded either as a variant of BP, from which it retains the property of low complexity, or as an approximation of a provably-convergent algorithm, from which it is expected to inherit better convergence properties. We investigate the algorithm behaviour on a real instance of Gallager code, and compare the results with state-of-the-art algorithms.
HuGeF (Sala Affrescata old building 1st floor "Aula Affrescata")
One of the hallmarks of cancer is to lose grip on growth control giving rise to a plethora of phenotypes: from disordered growth to invasion of adjacent tissues. I will discuss two paradigms of normal growth mechanisms gone awry.
Cultured epithelial cells can form cysts, i.e. perfectly ordered spheroidal monolayers delimiting a single lumen. The orderly development of cysts is a process subject to mechanical constraints and depends on apico-basal polarity. I will present experimental data and modeling results on cystogenesis and on the mechanisms that lead to a disrupted architecture. Our results indicate that dynamics has an important role in leading to aberrant phenotypes.
Oftentimes, once normal architecture is disrupted, migration of tumor cells to secondary sites becomes more probable. I will describe how metastatic cancer cells in three-dimensional environments can collectively migrate as spheroids and fuse into larger and larger aggregates. I will describe a theoretical model that explains the experimental data in terms of 'chemotaxis driven aggregation'. Theoretical hypotheses are supported by experimental data pointing at an autocrine loop at the basis of such behavior.
The coordination of cell growth and division is a long-standing problem in biology. In particular, the mechanisms that ensure size homeostasis and, at the same time, adapt cell growth and size to the environment have been the subject of intense research. However, the answers were traditionally hindered by limited statistics on single cells. Contemporary experimental techniques overcome this problem, but this progress must be combined with new theoretical tools to approach the data. Focusing on E. coli, we introduced a quantitative method for estimating the variables controlling the division rate from dynamic data, and used it to build a minimal stochastic model of cell growth and division. Combining this method with large-scale microscopy experiments, classic quantitative laws relating cell size, doubling time and growth rate of bacterial populations in different nutrient conditions can be revisited at the single cell level. The main result is the emergence of a combination of universality and individuality in the growth-division laws of single E. coli cells. These two apparently contrasting behaviors emerge naturally from the condition-dependent modulation of the division control mechanism, thus actually representing two sides of the same coin. Finally, the simultaneous observation of cell growth and DNA replication dynamics allowed us to pinpoint replication initiation and cell division as the two main "checkpoints" for size control. This opens the way to more detailed models of the process, and to rigorous tests of molecular cell-cycle descriptions.