probability

Effects of migration and stochasticity in subdivided populations

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.

Date: 
Thu, 22/01/2015 - 14:30
Speaker: 
Luca Dall'Asta (Polito)
Place: 
HuGeF, Via Nizza 52, Old Building, First floor, aula affrescata

Protein contact prediction: prospects and reality

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.

Date: 
Thu, 15/01/2015 - 14:30
Speaker: 
Marcin J. Skwark (The Finnish Centre of Excellence in Computational Inference)
Place: 
HUGEF, old building 1st floor "Aula Affrescata"

Bayesian inference of epidemics on network

I study inference problems for irreversible stochastic epidemic models on network via Belief Propagation algorithm. Previous works derive equations which allow to compute posterior distributions of the time evolution of the state of each node given some observation. It has already been shown that this method outperforms previous ones in the particular case of finding "patient zero" of a SIR epidemic given an observation at a later unknown time. I study performances of this method on the inference of the time evolution of a SIR epidemic subsequent a given observation.

Date: 
Thu, 16/10/2014 - 14:30
Speaker: 
Jacopo Bindi

Signal localization as a phase separation process

It is well known that ultrasensitivity (Goldbeter & Koshland, 1981) is the core of many bistable switches in biological systems. It is not as well recognized that when ultrasensitive self-amplifying circuits are diffusively coupled in a spatially distributed system such as the cell plasmamembrane, they may induce its dynamic separation into distinct signaling phases. This basic mechanism lays behind the process of cell membrane polarization in many, diverse biological systems. Cell membrane polarization is implicated in basic biological phenomena such as differentiation, proliferation, migration and morphogenesis of unicellular and multicellular organisms. Physical models based on the coupling of membrane diffusion with bistable enzymatic dynamics can reproduce a broad range of symmetry-breaking events, such as those observed in eukaryotic directional sensing, the apico-basal polarization of epithelial cells, the polarization of budding and mating yeast.

Date: 
Thu, 16/01/2014 - 14:30
Speaker: 
Andrea Gamba
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