Martin Lenz

Affiliation: CNRS - Université Paris-Saclay - ESPCI

Title: Slimming down through frustration

Abstract: In many diseases, proteins aggregate into fibers. Why? One could think of molecular reasons, but here we try something more general. We propose that when particles with complex shapes aggregate, geometrical frustration builds up and fibers generically appear. Such a rule could be very useful in designing artificial self-assembling systems.

Sebastian Furthauer

Affiliation: Institute of Applied Physics, TU Wien

Title: The physics of highly crosslinked cytoskeletal networks.

Abstract: Living cells move, deform and divide. The engine of these behaviors is the cytoskeleton, a highly crosslinked network of polymer filaments and molecular scale motors that use chemical energy to do work. We develop analytic theory that predicts how the micro-scale properties of molecular motors and crosslinks tune the networks emergent material properties and generate predictable, and possibly controllable, behaviors. I will present how this theory is constructed, and discuss its implications for cytoskeletal networks in vitro and in vivo.

William Podlaski

Affiliation: FC Champalimaud

Title: Computation in the balanced regime in low-rank excitatory-inhibitory spiking networks

Abstract: Deep feedforward and recurrent neural networks have become successful functional models of the brain, but they neglect obvious biological details such as spikes and Dale's law (the separation between excitatory and inhibitory neurons). Here we argue that these mechanistic details are crucial in order to understand how real neural circuits operate. Towards this aim, we put forth a new framework for spike-based computation in low-rank excitatory-inhibitory spiking networks, and contrast it with other, more traditional approaches for thinking about neural computation. By considering populations with rank-1 connectivity, we cast each neuron's spiking threshold as a boundary in a low-dimensional input-output space. We then show how the combined thresholds of a population of inhibitory neurons form a stable boundary in this space, and those of a population of excitatory neurons an unstable boundary. Combining the two boundaries results in a rank-2 EI network with inhibition-stabilized dynamics at the intersection of the two boundaries. The computation of the resulting networks can be understood as the difference of two convex functions, and is thereby capable of universal function approximation. We demonstrate several additional properties of these networks, including noise suppression and amplification, irregular activity and synaptic balance, as well as how they relate to rate network dynamics in the limit that the boundary becomes soft. Overall, our work proposes a new perspective on spiking networks that may serve as a starting point for a mechanistic understanding of biological spike-based computation.

Severine Atis

Affiliation: Institut Pprime, CNRS

Title: Growing in flows: from scaling laws to microbial jets

Abstract: Biological systems can self-organize in complex structures, able to evolve and adapt to widely varying environmental conditions. In this talk, I will illustrate how simple growth dynamics, when coupled with environmental properties, can lead to a diversity of self-organization phenomena in two experimental model systems: reaction waves propagating in disordered flows, and living microorganisms growing on viscous substrates. Resulting from the balance between molecular diffusion and nonlinear chemical kinetics, autocatalytic reactions can generate self-sustained fronts which propagate like progressive waves. I will show that in the presence of a disordered flow, the front fluctuations display scaling laws consistent with the universal behavior predicted by the Kardar-Parisi-Zhang stochastic growth model. Controlled by the mean flow amplitude, the system encompasses three distinct universality classes associated with different front morphologies and dynamical behaviors. In a second system, I will focus on mutual interactions between microbial growth and fluid flows. I will show that the metabolic activity of an expanding population of microorganisms can produce strong hydrodynamical flows when grown on top of a viscous medium. These flows in turn affect the growth dynamics, and can drive positive feedback phenomena such as accelerated propagation, fragmentation of the initial colony and the formation of growing microbial jets.

Omer Karin

Affiliation: Imperial College

Title: Self-organization of long-term biological memory

Abstract: Many biological systems, including epigenetic and immune memory systems, exhibit prolonged but finite responses. In this talk, I will present our analysis of two distinct memory systems: transgenerational gene silencing in C. elegans worms, and plasma cell persistence following immune responses in mice and humans. Despite utilizing different biological mechanisms, these systems share essential mathematical similarities that are captured by a general theory of self-tuning by competition to the vicinity of a noisy saddle-node bifurcation. The theory makes specific predictions, which we used to analyze a broad range of phenomena, including the buildup of memory, heterogeneity within and between responses, and the effect of perturbations. I will conclude by discussing how the self-tuning mechanism can be utilized as a basis for controlling biological systems.

Steffen Werner

Affiliation: Wageningen University

Title: Worms through the eyes of a physicist: From phase transitions in gene expression data to optimality in behaviour

Abstract: Patterns in biology typically arise from the intricate interplay between many constituents. Physics has a successful history in navigating and providing insights in such complex and high-dimensional datasets by means of minimal models and effective theories. My group uses flatworms and nematode worms as simple model systems in combination with physics-inspired theories to understand design principles from allometric scaling laws in body patterning to neural control of behaviour. In my talk, I will mainly focus on two examples using C. elegans worms: a novel approach to analyse noisy gene expression data and insights about optimality in animal locomotion.

Nuno Araujo


Affiliation: FCUL



Title: Modeling biological matter at microscale: from cells to tissues

Abstract: 


Abstract: The modeling of biological matter such as cells and tissue is ambitious. It not only involves processes at length and time scales over several orders of magnitude, but also biochemical processes occurring in the interior of the cell are likely to be relevant. In addition, in complex environments they are able self-propel, grow, divide, change shape, and respond slowly with memory, posing several changes to their theoretical model. In this talk, we will discuss how he have been combining theoretical modeling and advanced computational techniques to develop coarse-grained model that can reach the relevant scales and still describe the desired phenomena. Examples will include the bacteria motility in the presence of static and moving obstacles, the proliferation of cells in granular beds, and the mechanics of cell tissues on substrates.

Maros Pleska

Affiliation: The Rockefeller University

Title: The structure of noise: Non-genetic individuality,changeability and inheritance in microbial behavior

Abstract: Clonal populations ofmicroorganisms thriving in constant and homogeneous environments often displayremarkable phenotypic diversity, often termed as phenotypic “noise”. Severalmolecular processes capable of generating such diversity have been elucidatedin the context of individual genes, but how the signatures of these processespropagate to shape the structure of non-genetic diversity in the context ofcomposite traits remains mostly unclear. I will introduce a generalexperimental and theoretical framework that recently allowed us to quantifybacterial swimming behavior, a highly dynamic and complex aspect of thephenotype, using a small number of orthogonal and interpretable behavioraltraits. I will also discuss how representing the whole-lifetime behavior ofindividuals by trajectories in a low-dimensional trait space allowed us todecompose trait variation into individual sources, thus providing acoarse-grained overview of the population and temporal structure of non-geneticdiversity. Finally, will I briefly outline how the described framework foranalyzing the behavior of microorganisms can be extended to more complexecological settings in order to probe the interplay between non-geneticdiversity, phenotypic plasticity, and ecological dynamics.

Bingkan Xue


Affiliation:University of Florida



Title: Internal cues and memory for population adaptationin varying environments



Abstract: To adapt to varying environments, organisms canrely on external cues to infer and express favorable traits. Such cues arevaluable for the population if they are informative about the environmental condition. We propose an alternative source of information, which comes frominternal states of the organisms, without them having to sense externalsignals. These internal states can become correlated with the externalenvironment through the process of selection, thus being available as internalcues. We argue that these internal states also serve as a form of memory thatallows organisms to exploit temporal structure in the environment to predictfuture conditions. The value of such memory for population adaptation is givenby the amount of information between the past and future environments. We illustrate these theoretical ideas with the example of seed dormancy by considering the dependence of the germination fraction on the seed age.

Saúl Ares

Affiliation: CNB-CSIC

Title: Regulation and Feedback in Biological Systems: From Epidemics to Organ Development

Abstract: In this seminar, I will provide an overview of our current research on diverse topics related to the complexities of biological systems. I will discuss epidemic dynamics and vaccination strategies, organ size precision and feedback control mechanisms in the developing Drosophila eye, the interplay of light and temperature on plant growth, and the genetic regulation and physical constraints in pattern formation in nitrogen-fixing filaments of cyanobacteria. I will highlight key findings and their implications, emphasizing the importance of multidisciplinary approaches, mathematical modeling, and simulations in advancing our understanding of complex biological systems. This blackboard talk intends to encourage discussion, and we can delve into particular details based on feedback and interests from the audience.

Anne-Florence Bitbol 

Affiliation: EPFL

Title: Impact of population spatial structure on mutant fixation, from models on graphs to the gut 

Abstract: Microbial populations often have complex spatial structures, with homogeneous competition holding only at a local scale. Population structure can strongly impact evolution, in particular by affecting the fixation probability of mutants. I will first discuss a general model for describing structured populations on graphs. I will show that by tuning migration asymmetry in the rare migration regime, the star graph transitions from amplifying to suppressing natural selection. I will also discuss the impact of increasing migration rates. The results from our model are universal in the sense that they do not hinge on a modeling choice of microscopic dynamics or update rules. Instead, they depend on migration asymmetry, which can be experimentally tuned and measured. Then I will show that the specific structure of the gut, with hydrodynamics and gradients of food and bacterial concentrations, can increase the fixation probability of neutral mutants. Our results can be rationalized by introducing an active population, which consists of those bacteria that are actively consuming food and dividing. Thus, the specific environment of the gut enhances neutral bacterial diversity.