Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : FRAPPANT (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : RWTH Aachen University — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : RWTH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2491250.0 €

Probabilistic programs describe recipes on how to infer statistical conclusions about data from a complex mixture of uncertain data and real-world observations. They can represent probabilistic graphical models far beyond the capabilities of Bayesian networks and are expected to have a major impact on machine intelligence. Probabilistic programs are ubiquitous. They steer autonomous robots and self-driving cars, are key to describe security mechanisms, naturally code up randomised algorithms for solving NP-hard problems, and are rapidly encroaching AI. Probabilistic programming aims to make probabilistic modeling and machine learning accessible to the programmer. Probabilistic programs, though typically relatively small in size, are hard to grasp, let alone automatically checkable. Are they doing the right thing? What’s their precision? These questions are notoriously hard — even the most elementary question “does a program halt with probability one?” is “more undecidable” than the halting problem — and can (if at all) be answered with statistical evidence only. Bugs thus easily occur. Hard guarantees are called for. The objective of this project is to enable predictable probabilistic programming. We do so by developing formal verification techniques. Whereas program correctness is pivotal in computer science, the formal verification of probabilistic programs is in its infancy. The project aims to fill this barren landscape by developing program analysis techniques, leveraging model checking, deductive verification, and static analysis. Challenging problems such as checking program equivalence, loop-invariant and parameter synthesis, program repair, program robustness and exact inference using weakest precondition reasoning will be tackled. The techniques will be evaluated in the context of probabilistic graphical models, randomised algorithms, and autonomous robots. FRAPPANT will spearhead formally verifiable probabilistic programming.

Mots-clés : formal verification,probabilistic programming,model checking,program verification,weakest preconditions,probabilistic models,formal methods,bayesian networks
Projet ERC : BioCircuit (Horizon 2020, appel 2015, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : Eindhoven University of Technology — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : TU/e
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1887180.0 €

Programmable biomolecular circuits have received increasing attention in recent years as the scope of chemistry expands from the synthesis of individual molecules to the construction of chemical networks that can perform sophisticated functions such as logic operations and feedback control. Rationally engineered biomolecular circuits that robustly execute higher-order spatiotemporal behaviours typically associated with intracellular regulatory functions present a unique and uncharted platform to systematically explore the molecular logic and physical design principles of the cell. The experience gained by in-vitro construction of artificial cells displaying advanced system-level functions deepens our understanding of regulatory networks in living cells and allows theoretical assumptions and models to be refined in a controlled setting. This proposal combines elements from systems chemistry, in-vitro synthetic biology and micro-engineering and explores generic strategies to investigate the molecular logic of biology’s regulatory circuits by applying a physical chemistry-driven bottom-up approach. Progress in this field requires 1) proof-of-principle systems where in-vitro biomolecular circuits are designed to emulate characteristic system-level functions of regulatory circuits in living cells and 2) novel experimental tools to operate biochemical networks under out-of-equilibrium conditions. Here, a comprehensive research program is proposed that addresses these challenges by engineering three biochemical model systems that display elementary signal transduction and information processing capabilities. In addition, an open microfluidic droplet reactor is developed that will allow, for the first time, high-throughput analysis of biomolecular circuits encapsulated in water-in-oil droplets. An integral part of the research program is to combine the computational design of in-vitro circuits with novel biochemistry and innovative micro-engineering tools.

Mots-clés : systems chemistry,in vitro synthetic biology,artificial cells,microfluidics
Projet ERC : PyroPop (Horizon 2020, appel 2015, Consolidator grants)
Domaine scientifique : Life Science
Panel : Cellular, Developmental and Regenerative Biology
Entité participante : Vlaams Instituut voor Biotechnologie — Pays : Belgique — Rôle : Partner
Acronyme de l'entité : VIB
Type d'entité : Recherche
Financement ERC de l'entité : 676229.16 €

Programmed cell death is essential for homeostasis, and its deregulation contributes to human disease. Inflammasome-induced pyroptosis of infected macrophages contributes to host defense against infections, but the concomitant release of inflammatory danger signals and leaderless cytokines is detrimental in chronic inflammatory diseases. The central hypothesis of the PyroPop ERC Consolidator project is that inflammasomes are cytosolic platforms that couple pathogen sensing to multiple programmed cell death modes. This is based on our preliminary data showing that inflammasomes can be triggered to switch from inflammatory pyroptosis to programmed necrosis and non-inflammatory apoptosis. This suggests that the (patho)physiological outcomes of inflammasome activation may be modulated for therapeutic purposes. However, the molecular machinery and effector mechanisms of pyroptosis, inflammasome-induced apoptosis and programmed necrosis are virtually unknown. My objectives are (i) to explore the cleavage events and subcellular dynamics of pyroptosis by proteomics and high-resolution time-lapse microscopy; (ii) to clarify the molecular mechanisms of pyroptosis and inflammasome-controlled cell death switching; and (iii) to address how inflammasome-associated cell death modes impact on anti-bacterial host defense and chronic inflammatory pathology in vivo through the identification of pyroptosis-selective biomarkers and clinical analysis of pyroptosis-deficient mouse models. The central hypothesis in this regard is that inflammasome-mediated secretion of leaderless cytokines (such as IL-1β and IL-18) and danger signals may be mechanistically coupled to pyroptosis, but not apoptosis induction. By clarifying the mechanisms of inflammasome-controlled programmed cell death, this project may set the path for the development of an entirely novel class of inflammation-modulating therapies that are based on converting inflammatory pyroptosis into non-inflammatory apoptosis.

Mots-clés : pyroptosis,apoptosis,inflammasome
Projet ERC : ACTIVATE (Horizon 2020, appel 2019, Proof of concept grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : Alta Voce — Pays : France — Rôle : Partner
Type d'entité : Organismes privés (hors enseignement)
Financement ERC de l'entité : 35000.0 €

Project ACTIVATE aims to bring to market real-time voice-transformation technologies based on ERC CREAM's research in emotion neuroscience, which can augment the value of spoken conversations by adding business-relevant control on emotional expressivity. For instance, in the context of a call-center conversation, our real-time voice transformations may make an angry client’s voice 10% less aggressive, reducing employee fatigue at the end of the day, or make an operator’s voice 10% more trustworthy, augmenting customer satisfaction after the call. Project ACTIVATE will (1) conduct market analyses and interviews of industrial players to identify relevant conversational situations in which the technologies can be tested (e.g. for a call-center, a customer calling to resiliate their contract), (2) identify precise conversation outcomes that have market value (e.g. retention rate after the call), (3) measure the impact of the voice transformation on these outcomes in a simulated test environment that is near the desired configuration in terms of performance and user performance and (4) use the technology’s measured impact on relevant variables (e.g. a X% increase of retention rate) to estimate the value of a minimally-viable product (MVP), to be taken to market by a startup company to be created at the end of the project.

Mots-clés : voice,emotion,signal processing,real time,neurosciences,digital voice assistants,call center,augmentative and assistive technology
Projet ERC : TRIREME (Horizon 2020, appel 2020, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : University of Edinburgh — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999928.75 €

Project TRIREME will explore the transport of energy through minerals and melts at the high pressure and temperature conditions of the Earth’s interior, and the consequences for Earth’s evolution and its present dynamics, from the core to the biosphere. Deep transport determines the age and growth behaviour of the inner core, the thermal history of the mantle, and the longevity of Earth’s life- and civilization-sustaining magnetic field. This project will determine the transport behaviour in deep Earth materials via cutting edge experiments at extreme conditions, constraining heat transport, electrical conduction, and fluid flow in Earth’s core and lower mantle. Accurate numerical modelling of the complex experiments will robustly establish underlying transport properties and their uncertainties. Applying these methods in geophysically-relevant minerals and melts, including iron alloys and mantle minerals, at the true conditions of Earth’s interior, our results will constrain the dynamics of deep Earth systems, to better understand and predict their evolution and effect on the surface environment. We will examine in particular the current and historic conditions of Earth’s core and dynamo-driven magnetic field in the context of geodynamic and geomagnetic constraints on deep dynamics. Project TRIREME (Latin: "three rows of oars") will thus comprise three lines of investigation: 1) the laboratory study of transport in Earth's interior using novel and cutting-edge experimental techniques at high pressure and temperature; 2) the numerical modelling of experiments in unprecedented detail to accurately characterise observed transport phenomena at extremes; and 3) consideration of the geodynamic phenomena emerging from the underlying transport behaviour. In breaking through longstanding challenges in the measurement of transport at extreme conditions, this work will set course to make a historic impact in the study of Earth systems’ dynamics.

Mots-clés : high,pressure,temperature,laser,heated,diamond,anvil,cell,thermal,conductivity,viscosity,experiment
Projet ERC : Matryoshka (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Université de Lorraine — Pays : France — Rôle : Partner
Acronyme de l'entité : UL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 75000.0 €

Proof assistants are increasingly used to verify hardware and software and to formalize mathematics. However, despite the success stories, they remain very laborious to use. The situation has improved with the integration of first-order automatic theorem provers -- superposition provers and SMT (satisfiability modulo theories) solvers -- through middleware such as Sledgehammer for Isabelle, codeveloped by the PI; but this research has now reached the point of diminishing returns. Only so much can be done when viewing automatic provers as black boxes. To make interactive verification more cost-effective, we propose to deliver very high levels of automation to users of proof assistants by fusing and extending two lines of research: automatic and interactive theorem proving. This is our grand challenge. Our starting point is that first-order automatic provers are the best tools available for performing most of the logical work. Our approach will be to enrich superposition and SMT with higher-order reasoning in a careful manner, to preserve their desirable properties. We will design proof rules and strategies, guided by representative benchmarks from interactive verification. With higher-order superposition and higher-order SMT in place, we will develop highly automatic provers building on modern superposition provers and SMT solvers, following a novel stratified architecture. To reach end users, these new provers will be integrated in proof assistants, including Coq, Isabelle, and the TLA+ Proof System, and will be available as backends to more specialized verification tools. The users of proof assistants and similar tools stand to experience substantial productivity gains: In the past five years, the success rate of automatic provers on interactive proof obligations from a representative benchmark suite has risen from 47% to 77%; with this project, we aim at 90%--95% proof automation.

Mots-clés : automatic theorem proving,interactive theorem proving,proof assistants,smt solvers,superposition
Projet ERC : NeurO-GI (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : Partner
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 0.0 €

Proper functioning of the digestive system depends largely on the enteric nervous system (the gut’s brain), which on one side is linked to the gut’s microbiota and on the other side is linked to environmental factors, like stress, via gut-brain axis. Communication along this axis is not very well understood, even though it is crucial for the diagnosis and treatment of functional digestive disorders, which are the most common problems in the digestive system imposing a significant burden on public health. One of the limiting factors is the lack of tools enabling investigation of gut’s neuronal network in vivo. The goal of this proposal is to provide an insight into the functioning of microbiota-gut-brain axis in vivo. We will develop a novel optogenetic endomicroscope based on Optical Coherence Tomography (OCT) capable of mapping the morphology and the functionality of the enteric nervous system and microbiota sampling. We hypothesize that such tool, in addition to direct analysis of the gut status in various digestive conditions, can also be indirectly used to stimulate the brain response via gut-brain axis. To test our hypothesis, we will co-register performance of the proposed method with functional magnetic resonance imaging to investigate in animal models 1) the response of the brain to activation of serotonin neurons in the gut and 2) the response of the gut to optogenetically induced depression at the brain level. Any tool improving understanding of interactions between microbiota, gut and brain would be of paramount importance for improving management of many patients with digestive disorders. Moreover, such information has potential to introduce novel diagnosis and treatment paradigm in obesity, and other diseases like Parkinson disease or Alzheimer disease. With the ultimate goal of transferring our finding into humans, we will be focused on finding OCT-specific designs and biomarkers for diagnosing diseases linked to dysfunction of this axis.

Mots-clés : nurogastroenterology,optical coherence tomography,optogenetics,optrode,gut brain axis,microbiota,inflammatory bowel disease,functional digestive disorders,motility,diagnosing and treatment
Projet ERC : EpiRep (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Life Science
Panel : Molecules of Life: Biological Mechanisms, Structures and Functions
Entité participante : Royal Netherlands Academy of Arts and Sciences — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : KNAW
Type d'entité : Recherche
Financement ERC de l'entité : 1500000.0 €

Proper inheritance of the epigenetic information during cell division controls cell fate decisions, tissues homeostasis and development, ensuring disease avoidance. We have little understanding however of the mechanisms by which epigenetic information, specifically histone post-translational modifications in nucleosomes, are replicated in parallel to the DNA prior to cell division. This process strictly depends on proper nucleosome formation on the newly synthesized DNA strands. Here, I will study the molecular mechanism of nucleosome assembly during DNA replication. Nucleosome dynamics during DNA replication is controlled by an interconnected network of histone chaperones that converges on the key Chromatin Assembly Factor 1 (CAF-1). I recently elucidated the molecular mechanism of CAF-1-mediated nucleosome assembly, in absence of any other replication components. I developed a quantitative (NAQ) assay that allows, for the first time, the quantification of nucleosome assembly activity in vitro. In cells, CAF-1 is recruited to replication forks by the DNA polymerase processivity factor PCNA. Here, I will capitalize and expand on the assays above to integrate structural data, quantitative biochemical and biophysical measurements, and functional analyses, to elucidate how CAF-1 crosstalks to PCNA, DNA polymerases and other components of the DNA replication machinery in S phase. Specifically, the proposed research will 1) uncover how CAF-1 recruitment by PCNA affects its function in nucleosome assembly, and 2) examine how CAF-1 activity is regulated during ongoing DNA replication. This work will reveal the mechanism of nucleosome assembly during DNA replication and its interplay with S phase signaling. A mechanistic understanding of this pathway will uncover the fundamental principles that control genome and epigenome stability, thus cell fate decisions and disease avoidance.

Mots-clés : chromatin,in vitro reconstitutions,histone chaperone
Projet ERC : ProteaseNter (Horizon 2020, appel 2017, Proof of concept grants)
Entité participante : University of Freiburg — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 149900.0 €

Protein N-termini represent a wealth of biological information, such as their generation by limited proteolysis, which sculpts proteome functionality by yielding protein-sized cleavage products with novel functionality. N-terminomics is a branch of functional proteomics and enables the analysis of thousands of protein N-termini in an unbiased manner. By targeting native, proteolytically generated or acetylated protein N-termini as well as uncovering novel translation initiation sites, N-terminomics bears relevance to proteolysis and proteogenomics research. Unlike proteomic assays to study modifications such as phosphorylation, N-terminomics has remained inaccessible to non-expert laboratories due to a lack of ready-to-use kit formats or commercial services. Based on a recently published N-terminomic workflow by my laboratory, the present project aims to fill this niche by laying the foundation to represent N-terminomics (sample preparation up to mass spectrometry analysis) in a kit-like format together with online data analysis. Development steps include inclusion of multiple internal standards for improved sample-to-sample comparability, sole usage of cost-effective, disposable “small-scale” equipment in sample preparation, minimization of required input material, adaption to different input material including cryopreserved and formalin-fixed, paraffin-embedded samples, as well as web-based mass spectrometry data analysis and annotation. This endeavor is based on multiple collaborative projects of the applicant with pharmaceutical companies and backed by interest of proteomic supply companies. In a small forward-looking activity, the project will explore the application N-terminomics in molecular diagnostics of bladder cancer; based on the rationale local infiltration by solid tumors is based on differential proteolysis. This activity serves an initial step to add N-terminomics to the toolbox of molecular pathology.

Mots-clés : proteolysis,functional proteomics,degradomics
Projet ERC : Proteomes-in-3D (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
Entité participante : Board of the Swiss Federal Institutes of Technology — Pays : Suisse — Rôle : PI
Acronyme de l'entité : ETH Zurich
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

Protein expression screens are routinely used to identify biological processes deregulated upon disease development or upon specific cellular perturbations. Generating molecular hypotheses from these ‘omic data remains challenging, however, and many molecular events that modulate protein function do not involve altered protein levels. With this project, I propose a new paradigm. I propose that by measuring altered structures of proteins on a global scale, we can capture altered functional states of proteins and proteomes. I propose that the new approach will support the generation of testable molecular hypotheses from global data and the development of new frameworks for the modelling of biological systems. Building on a unique mass spectrometric approach my lab developed, which captures protein structural changes on a proteome-wide scale, we will assess the performance of the global structural readout at analyzing complex phenotypes. We will apply it to a biomedical problem of interest to my lab: the functional and pathological implications of protein aggregates or superassemblies (SAs). Protein aggregates form not only during disease but also under physiological conditions. These structures regulate important normal processes and contribute to cellular architecture. Using the new structural approach, we will identify and characterize networks of novel functional SAs in E. coli, mouse, and human proteomes. We will assess how genomic variation, environment and age modulate protein structures and SA assembly and how SAs are linked to phenotypes. Last, we will translate our approach to a clinical setting and ask whether altered protein structures can serve as biomarkers of disease, specifically Parkinson’s disease and how SAs underlie Parkinson’s subtypes. We will collect the wealth of dynamic structural data generated through this project into an Atlas of Structural Proteome Dynamics and use the data to shed new light on features of the structural proteome.

Mots-clés : proteomics,structural proteomics,protein aggregation,metabolism,parkinson s disease,alpha synuclein,structural systems biology