Motivated by a question about the sensitivity of knots’ diffusive motion to the actual sequence of nucleotides placed on a given DNA, here we study a simple model of a sequence-reading diffu- sion on a stretched chain with a frozen sequence of “letters” A and B, having different interaction energies. The chain contains a single distortion - a hernia - which brings the two letters at its bottom...
Morphogenesis, the process through which genes generate form, establishes tissue scale order as a template for constructing the complex shapes of the body plan. The extensive growth required to build these ordered substrates is fueled by cell proliferation, which, naively, should disrupt order. Understanding how active morphogenetic mechanisms couple cellular and mechanical processes to...
To improve the storage capacity of the Hopfield model, we develop a version of the dreaming al-
gorithm that perpetually reinforces the patterns to be stored (as in the Hebb rule), and erases the
spurious memories (as in dreaming algorithms). For this reason, we called it Daydreaming. Day-
dreaming is not destructive and it converges asymptotically to stationary retrieval maps. When
trained on...
The 3D folding of mammalian DNA (chromatin) is tightly linked to its transcriptional activity, hence its understanding constitutes an important goal in biophysics. In this talk I present a poly- mer physics model to study the 3D folding of a chromatin segment. We find by simulations that, out of the sleuth of a priori possible topologies, only a handful are observed, characterised by an...
Polymer translocation — the process of pulling single filamentous molecules through narrow pores — has long been studied as an example of out-of-equilibrium statistical mechanics and for its rel- evance in DNA sequencing and biological processes. However, the case in which the polymer structure itself is deeply altered by translocation remains largely unexplored. Here, we address this...
Chromatin is a complex biopolymer of DNA and proteins that not only packages the genetic material in the nucleus but also controls gene expression. The interactions that stabilise the three-dimensional structure of chromatin are mediated by different proteins, often through out-of- equilibrium mechanisms. We have developed some powerful models to describe such interactions by averaging the...
We investigate a large set of electronic health records (EHRs) collected by wellbeing services county of Soutwest Finland (Varha) [1]. Different diseases have different prevalence in a given population. For this reason, the observation of a specific comorbidity in a given patient could be just the result of a random co-occurrence of two unrelated diseases. Therefore a comorbidity net- work of...
I will recap our effort to represent populations of cells using Maximum-Entropy models defined on the space of single-cell metabolic states. At odds with more conventional optimization-based theories, these models place the emphasis on (a) cell-to-cell variability, (b) its relationship with fitness, and (c) inter-cellular interactions. Advantages, limitations and challenges will hopefully...
Stochastic resonance (SR) phenomena provide insight into the behavior of complex biological sys- tems. Furthermore, a method for characterizing SR-type behavior in excitable systems with ape- riodic and arbitrary inputs, such as broadband signals, has been developed and termed aperiodic stochastic resonance (ASR). It was discovered that noise can enhance the response of a sensory neu- ron to a...
Healthy brains exhibit a rich dynamic repertoire with flexible and diverse spatiotemporal pattern replays across microscopic and macroscopic scales.We hypothesize that the system must operate near a critical regime for the functional repertoire to be fully explored, and flexible dynamics to emerge.To test this hypothesis, we employ a modular Spiking Neuronal Network model, where each group of...
Leveraging the large body of work devoted in recent years to describe redundancy and synergy in higher order interactions among random variables, we propose an adaptive version of a well- known metric of feature importance, named Leave One Covariate Out (LOCO), to disentangle high- order effects involving a given input feature in regression problems. Applications to biological data sets will...
Heterogeneous and complex networks represent the intertwined interactions between real-world elements or agents. Determining the multi-scale mesoscopic organization of clusters and inter- twined structures is still a fundamental and open problem of complex network theory. By taking advantage of the recent Laplacian Renormalization Group [1-4] approach , we scrutinize informa- tion diffusion...
Protein fitness landscapes frequently exhibit epistasis, where the effect of a mutation depends on the genetic context, i.e., the rest of the protein sequence. Epistasis increases landscape complexity, often resulting in multiple fitness peaks. In its simplest form, known as global epistasis, fitness is modeled as a non-linear function of an underlying additive trait. In contrast, more complex...
The advent of deep learning algorithms for protein folding opened a new era in the ability of pre- dicting and optimizing the function of proteins once the sequence is known. The task is more intricate when cofactors like metal ions or small ligands are essential to functioning. In this case, the combined use of traditional simulation methods based on interatomic force fields and deep learning...
Over the last decade, the combined development of accurate time- resolved experimental tech- niques and advanced algorithms for computer simulations has opened the possibility of investigat- ing biological mechanisms at atomic resolution with physics-based models. In particular, combi- nation of experimental information and enhanced sampling techniques now allow the reconstruc- tion of the co-...
Gene regulation is a complex web across biological levels, and its intricacy often complicates pre- cise interventions, with off-target effects being a major hurdle. To transform this, we here propose a photoactivatable microRNA-based circuit that enables unmatched accuracy in gene targeting, po- tentially reducing off-target effects. Our approach leverages the concept of microRNAs (miRNAs) as...
I will review some concepts and applications of Reinforcement Learning to modeling of animal behavior
Unlike gas molecules at equilibrium, the spatial organization of self-propelled particles can be very sensitive to what happens at the boundaries of their container. Understanding the link between boundary phenomena and bulk stationary distributions could enable the design of optimized con- tainer shapes for the geometric control of confined active particles. Here we propose a boundary method...
Marker genes are genes that have expression profiles able to distinguish the sub-populations of cells present in the data. They are used to annotate cell types and “understand” their biology. In cancerous tissues they are used to identify cancer subtypes and thus to fine-tune therapies. Complex pathologies (in particular cancer) are characterized by strong variability at the molecular level....
Cellular signaling pathways operate as nonequilibrium biochemical networks that transduce di- rected chemical or mechanical signals across the cell. These cascades, initiated for example by ligand binding to membrane receptors, involve multiple biochemical reactions and complex for- mations. Because signaling pathways rely on branched, multiplicative processes, errors can propagate rapidly,...
Proliferating cells organize their resources in order to harness nutrients from the environment and grow. Work in bacteria has highlighted how this behavior leads to striking emergent “growth laws” linking growth to cellular composition. However, beyond bacteria, we still have limited insight on the generality of such laws and even in bacteria some of the key mechanistic aspects underlying...
Eukaryotic cells maintain their internal order through a hectic process of sorting and distillation of molecular factors taking place on their lipid membranes. A similar sorting process is implied in the assembly and budding of enveloped viruses. We have proposed a theoretical model of the process, in which molecular sorting emerges from the coupling of phase separation and membrane bending....
Molecular sorting is a vital process in eukaryotic cells, where proteins and other biomolecules are sorted and encapsulated into lipid vesicles for targeted transport to specific organelles and sub- cellular locations. Recent studies suggest this process is driven by a physical mechanism based on phase separation, in which the formation and growth of sorting domains depends primarily on direct...
We present a minimal reaction-diffusion model that describes the behavior of molecules on a lipid membrane interacting with the surrounding cytosol. In this model, due to a feedback mechanism in chemical reactions, molecules phase separate into distinct domains. Unlike classical phase separation, this phenomenon is driven by enzymatic reactions, introducing an active component to the system....
Motivated by a question about the sensitivity of knots' diffusive motion to the actual sequence of nucleotides placed on a given DNA, here we study a simple model of a sequence-reading diffusion on a stretched chain with a frozen sequence of "letters" A and B, having different interaction energies. The chain contains a single distortion - a hernia - which brings the two letters at its bottom...
We develop a novel mother machine-like microfluidic device designed to track the proliferation of single mammalian cells via live-cell microscopy.
Although numerous microfluidic devices have been developed to study cell proliferation at the single-cell level, most of them are optimized for bacteria, which do not require particularly demanding growth conditions.
We present a device specifically...
Over the last decade, the combined development of accurate time-
resolved experimental techniques and advanced algorithms for
computer simulations has opened the possibility of investigating
biological mechanisms at atomic resolution with physics-based
models. In particular, combination of experimental information and
enhanced sampling techniques now allow the reconstruction of the...
We study analytically and numerically the transport properties of an active tracer in a schematic crowded environment, represented as a lattice gas of passive particles with hardcore interactions. We focus on diffusion coefficient and
mobility of the active particle and show that our approach correctly captures surprising nonequilibrium effects, which are the signature of the activity in the...
The Wang-Landau algorithm is a powerful Monte Carlo method designed to reconstruct self-consistently the density of states of a system by uniformly exploring the energy spectrum. This approach allows the efficient sampling of otherwise rare configurations, making it particularly well-suited for systems with rugged energy landscapes. In this work, we present a continuous variant of the...
The calorimetric criterion is one of the experimental approaches used in the last decades, in particular in the context of protein folding, for assessing the cooperativity of many biophysical processes, modelled as transitions between a high temperature to a low temperature state. In a maximally cooperative two-state transition, no intermediate states are present at equilibrium, implying that...
The human cis-prenyl-transferase is an enzyme involved in isoprenoid synthesis formed by a catalytic subunit and an auxiliary subunit. The purpose of our work was to understand the mechanism through which the S249V mutation, outside the catalytic subunit, can affect the activity of the enzyme.
We first built a protein network where the arc weights were related to the correlation of the two...
Predicting interactions between proteins is fundamental since protein–protein complexes are crucial in physiological and pathological processes. Despite this, understanding the binding process is challenging: binding partners must find each other amid thousands of other molecules in the crowded cell. This binding specificity is determined by a complex combination of matches at the interfaces....
Trypanosomes's mitochondrial genome (kinetoplast DNA, kDNA) is made of many interlinked DNA circles. In the case of Crithidia fasciculata, the kDNA consists of a network of about 5000 semi-flexible minicircles that form a chain-mail-like 2D network and a couple dozen interlaced maxicircles located at the network's border. In vivo it has a diameter of $d=1\mu m$ while, once extracted, presents...
Microbial communities are known to play an extraordinary role in maintaining life on our planet. Such communities are characterized by a complex network of interactions and typically reside in environments that fluctuate over time. For example, natural bacterial isolates positively interact by exchanging building blocks: bacteria are often unable to produce one or more amino acids...
To improve the storage capacity of the Hopfield model, we develop a version of the dreaming algorithm that perpetually reinforces the patterns to be stored (as in the Hebb rule), and erases the spurious memories (as in dreaming algorithms). For this reason, we called it Daydreaming. Daydreaming is not destructive and it converges asymptotically to stationary retrieval maps. When trained on...
Many studies of biological systems are conducted in simple and dilute conditions, with macromolecular concentrations below 10 g/L—far lower than those typically found in living media. The extracellular matrix (ECM), for example, which forms the structural framework of tissues and organs, is a highly dense and complex environment. More precisely, the ECM provides a crowded and confining...
Stochastic resonance (SR) phenomena provide insight into the behavior of complex biological systems. Furthermore, a method for characterizing SR-type behavior in excitable systems with aperiodic and arbitrary inputs, such as broadband signals, has been developed and termed aperiodic stochastic resonance (ASR). It was discovered that noise can enhance the response of a sensory neuron to a...
Hi-C contact matrices capture the three-dimensional organization of chromatin by quantifying physical proximities between genomic loci. Interpreting these matrices as adjacency representations of complex networks opens interesting perspectives on their structural analysis using tools such as spectral graph theory. In this talk, we will investigate the spectral properties — particularly...
We introduce a data-driven epistatic model of protein evolution, capable of generating evolutionary trajectories spanning very different time scales reaching from individual mutations to diverged homologs. Our in silico evolution encompasses random nucleotide mutations, insertions and deletions, and models selection using a fitness landscape, which is inferred via a generative probabilistic...
The 3D folding of mammalian DNA (chromatin) is tightly linked to its transcriptional activity, hence its understanding constitutes an important goal in biophysics. In this talk I present a polymer physics model to study the 3D folding of a chromatin segment. We find by simulations that, out of the sleuth of a priori possible topologies, only a handful are observed, characterised by an...
Randomly branching polymers provide a valuable framework for studying genome organization: Tree-like double-folded structures of ring polymers in melt conditions [1,2] resemble eukaryotic DNA during interphase on scales above several kilo base pairs [3,4]. Moreover, extensive supercoiling causes circular bacterial DNA to adopt branched structures [5].
Much of the structural complexity of...
Leveraging the large body of work devoted in recent years to describe redundancy and synergy in higher order interactions among random variables, we propose an adaptive version of a well-known metric of feature importance, named Leave One Covariate Out (LOCO), to disentangle high-order effects involving a given input feature in regression problems. Applications to biological data sets will be...
The phosphatase protein SHP2 plays a crucial role in regulating key cellular signaling pathways. Activating mutations in SHP2 have been linked to developmental disorders such as Noonan syndrome and are associated with multiple cancer types [1,2]. SHP2 has a multi-domain structure comprising two SH2 domains (N-SH2 and C-SH2) followed by a catalytic PTP domain. SH2 domains recognize and bind...
Understanding criticality in neural networks is essential for deciphering brain function and detecting pathological deviations. However, neural recordings capture only a fraction of the entire system, and subsampled dynamics may not fully reflect global behavior. In this study, we analyze two stochastic models, the mean-field branching process and (2+1)D directed percolation, to investigate...
Development relies on the finely coordinated expression of morphogens, proteins driving cell differentiation and organ formation. Cell fate specification is achieved thanks to the establishment of morphogen patterns, which act as signals for cells in a concentration dependent manner. By the aid of reaction-diffusion systems, intense studies over the past decades were dedicated to the...
Generative probabilistic models have shown promise in designing artificial RNA and
protein sequences but often suffer from high rates of false positives, where sequences
predicted as functional fail experimental validation. To address this critical limita-
tion, we explore the impact of reintegrating experimental feedback into the model
design process. We propose a likelihood-based...
Proliferating cells organize their resources in order to harness nutrients from the environment and grow. Work in bacteria has highlighted how this behavior leads to striking emergent "growth laws" linking growth to cellular composition. However, beyond bacteria, we still have limited insight on the generality of such laws and even in bacteria some of the key mechanistic aspects underlying...
Marker genes are genes that have expression profiles able to distinguish the sub-populations of cells present in the data. They are used to annotate cell types and “understand” their biology. In cancerous tissues they are used to identify cancer subtypes and thus to fine-tune therapies.
Complex pathologies (in particular cancer) are characterized by strong variability at the molecular level....
Asymmetric partition of fate determinants during cell division is a hallmark of cell differentiation. Recent works suggested that such a mechanism is hijacked by cancer cells to increase both their phenotypic heterogeneity and plasticity and in turn their fitness. To quantify fluctuations in the partitioning of cellular elements, imaging-based approaches are used, whose accuracy is limited by...
Unlike gas molecules at equilibrium, the spatial organization of self-propelled particles can be very sensitive to what happens at the boundaries of their container. Understanding the link between boundary phenomena and bulk stationary distributions could enable the design of optimized container shapes for the geometric control of confined active particles. Here we propose a boundary method...
Molecular sorting is a vital process in eukaryotic cells, where proteins and other biomolecules are sorted and encapsulated into lipid vesicles for targeted transport to specific organelles and sub-cellular locations. Recent studies suggest this process is driven by a physical mechanism based on phase separation, in which the formation and growth of sorting domains depends primarily on direct...
Morphogenesis, the process through which genes generate form, establishes tissue scale order as a template for constructing the complex shapes of the body plan. The extensive growth required to build these ordered substrates is fueled by cell proliferation, which, naively, should disrupt order. Understanding how active morphogenetic mechanisms couple cellular and mechanical processes to...
Phase separation of chimeric proteins resulting from genetic mutations has been shown to trigger aberrant chromatin looping, contributing to disease development, including cancer [1]. However, the physical mechanisms regulating these processes remain unclear. In this study, we employ polymer physics models of chromatin to investigate the relationship between protein self-aggregation and...
The advent of deep learning algorithms for protein folding opened a new era in the ability of predicting and optimizing the function of proteins once the sequence is known. The task is more intricate when cofactors like metal ions or small ligands are essential to functioning. In this case, the combined use of traditional simulation methods based on interatomic force fields and deep learning...
I will review some concepts and applications of Reinforcement Learning to modeling of animal behavior
Understanding macroscopic phenomena in complex systems requires accurate modeling of stochastic dynamics in structured interactions. We present a computational framework based on dynamic cavity equations for stochastic processes on sparse networks. Using a second-order small-coupling expansion, we approximate cavity marginals as Gaussian. For linear dynamics with additive noise,...
We investigate a large set of electronic health records (EHRs) collected by wellbeing services county of Soutwest Finland (Varha) [1]. Different diseases have different prevalence in a given population. For this reason, the observation of a specific comorbidity in a given patient could be just the result of a random co-occurrence of two unrelated diseases. Therefore a comorbidity network of...
Heterogeneous and complex networks represent the intertwined interactions between real-world elements or agents. Determining the multi-scale mesoscopic organization of clusters and intertwined structures is still a fundamental and open problem of complex network theory. By taking advantage of the recent Laplacian Renormalization Group [1-4] approach , we scrutinize information diffusion...
Healthy brains exhibit a rich dynamic repertoire with flexible and diverse spatiotemporal pattern replays across microscopic and macroscopic scales.We hypothesize that the system must operate near a critical regime for the functional repertoire to be fully explored, and flexible dynamics to emerge.To test this hypothesis, we employ a modular Spiking Neuronal Network model, where each group of...
Biological and living organisms sense and process information from their surroundings, typically having access only to a subset of external observables for a limited amount of time. Here, we uncover how biological systems can exploit these accessible degrees of freedom to transduce information from the inaccessible ones with a limited energy budget. We find that optimal transduction strategies...
Polymer translocation — the process of pulling single filamentous molecules through narrow pores — has long been studied as an example of out-of-equilibrium statistical mechanics and for its relevance in DNA sequencing and biological processes. However, the case in which the polymer structure itself is deeply altered by translocation remains largely unexplored. Here, we address this phenomenon...
