Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : TSGPs-of-CFSs (Horizon 2020, appel 2015, Consolidator grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : Hebrew University of Jerusalem — Pays : Israël — Rôle : PI
Acronyme de l'entité : HUJI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

Common fragile sites (CFSs) are large chromosomal regions identified by conventional cytogenetics as sequences prone to breakage in cells subjected to replication stress. The interest in CFSs stems from their key role in DNA damage, resulting in chromosomal rearrangements. The instability of CFSs was correlated with genome instability in precancerous lesions and during tumour progression. Two opposing views dominate the discussion regarding the role of CFSs. One school of thought suggested that genomic instability during cancer progression causes collateral damage to genes residing within CFSs, such as WWOX and FHIT. These genes are proposed to be unselected ‘‘passenger’’ mutations. The counter argument is that deletions and other genomic alterations in CFSs occur early in cancer development. Cancer cells with deletions in genes that span CFSs are then selectively expanded due to loss of tumour suppressor functions such as protection of genome stability, coordination of cell cycle or apoptosis. Recent observations from my lab clearly suggest that gene products from CFSs play driver roles in cancer transformation. Moreover, we have evidence for the involvement of DNA damage and Wwox in pancreatic β-cells in the context of diabetes. Here, I propose to investigate the role of tumour suppressor gene products (TSGPs) of CFSs in human diseases. Three approaches will be taken to tackle this question. First, molecular functions of TSGPs of CFSs will be determined using state-of-the-art genetic tools in vitro. Second, novel transgenic mouse tools will be used to study CFSs and their associated TSGs in preneoplastic lesions and tumours in vivo, with confirmatory studies in human material. Third, we will examine the potential involvement of CFSs and their TSGPs in type-2 diabetes (T2D). The expected outcome is a detailed molecular understanding of CFSs and their associated TSGPs in genomic instability as well as their roles in cancer and metabolic diseases.

Mots-clés : cancer mouse models,genomic instability,diabetes,wwox,fra16d
Projet ERC : FACEDIFF (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : Nottingham Trent University — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : NTU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1786790.63 €

Communicating with others via the face is crucial for navigating our social world. Deficits in facial expression production can have debilitating effects on social interaction, characterising several clinical conditions such as autism spectrum disorder, schizophrenia and Parkinson’s disease. Despite this, we know surprisingly little about individual differences in facial expressivity in the typical population, what causes these differences and whether such differences impact on individual lives. In part, this could be due to an historical focus on the universal nature of facial expression, assigning individual difference to random ‘noise’, rather than an evolutionarily relevant characteristic. The FACEDIFF project will diverge from this classic approach and test the novel hypothesis that individual differences in facial expressivity equip individuals’ differentially to engage with their social environment: expressivity has a benefit (social engagement) but also a cost (over-exposure and thus risk of being cheated by others) and is related to the size and quality of an individual’s social network. FACEDIFF will combine psychological, anatomical and cross-species methods to provide the first thorough interdisciplinary investigation of individual differences. First, individual variation in production and perception of facial expressions will be measured via laboratory experiments and in relation to social network size and quality. Second, variation in human facial musculature will be documented through cadaveric dissection and existing MRI databases. Third, facial expressivity will be examined in a primate model to determine whether patterns are unique to humans. This project will be the first to provide a comprehensive and interdisciplinary perspective on individual differences in facial expression and will stimulate new theories on the function and evolution of individual differences in humans.

Mots-clés : facial expression,communication,universality,anatomy,evolution
Projet ERC : inCREASE (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : Technical University of Munich — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : TUM
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1471750.0 €

Communication and data storage systems are indispensable parts of our every-day life. However, these systems deal with severe challenges in security and reliability. Security is important whenever a user communicates or stores sensitive data, e.g., medical information; reliability has to be guaranteed to be able to transmit or store information while noise occurs. Algebraic codes (ACs) are a powerful means to achieve both. Within inCREASE, I will construct and evaluate special codes for security applications and DNA storage. The tasks are structured into three work packages: (1) post-quantum secure code-based cryptosystems, (2) secure key regeneration based on ACs, (3) ACs for DNA-based storage systems. The focus of inCREASE lies on innovative theoretical concepts. The goal of work package (1) is to investigate and design code-based cryptosystems; one promising idea is to apply insertion/deletion correcting codes. The security of these systems will be analysed from two points of view: structural attacks on the algorithms and hardware implementations with side-channel attacks. Secure cryptographic key regeneration is the goal of (2) and can be achieved by physical unclonable functions (PUFs). Here, ACs are necessary to reproduce the key reliably. This project will study the error patterns that occur in PUFs, model them theoretically, and design suitable coding schemes. The investigation on (3) will start with a study of the data of existing DNA storage systems. The outcome will be an error model that will include insertions, deletions, substitutions, and duplications. Therefore, inCREASE will design ACs for these error types. This will be especially challenging regarding the mathematical concepts. These codes will be evaluated by simulations and using data sets of DNA storage systems. This project is high risk/high gain with impact not only to storage and security, but to the methodology as well as other areas such as communications.

Mots-clés : coding theory,error correcting codes,code based cryptography,coding for dna storage,channel coding
Projet ERC : SMART DESIGN (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed matter physics
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 1376000.0 €

Compared to existing Random Access Memories, the Magnetic RAM (MRAM) has the advantage of being non-volatile. Though the basic requirements for reading and writing a single memory element are fulfilled, the present approach based on Spin Transfer Torque (STT) suffers from an innate lack of flexibility. The solution that I propose is based on the discovery of a novel phenomenon, where instead of transferring spin angular momentum from a neighbouring layer, magnetization reversal is achieved by angular momentum transfer directly from the crystal lattice. There is a long list of advantages that this novel approach has compared to STT, but the goal of this project is to focus only on their most generic difference: flexibility. The singularity of spin-orbit torque is that the in-plane current injection geometry decouples the “read” and “write” mechanisms. The disconnection is essential, as unlike STT where the pillar shape of the magnetic trilayer sets the current path, in the case of SOT the composing elements may be shaped separately. The liberty of shaping the current distribution allows to spatially modulate the torque exerted on the local magnetization. The central goal of my project is to explore the new magnetization dynamics, specific to the Spin-Orbit Torque (SOT) geometry, and design novel magnetization switching schemes. I will begin by tackling the fundamental questions about the origin of SOT and try to control it by mastering its dependence on the layer structure. Materials with on-demand SOT will serve as playground for the testing of a broad range of magnetization reversal techniques. The most successful among them will become the building-blocks of complex magnetic objects whose switching behaviour is tightly related to their shape. To study their magnetization dynamics I plan to build a time-resolved near-field magneto-optical microscope, a unique tool for the ultimate spatial and temporal resolution.

Mots-clés : magnetization dynamics,spin orbit interaction,rashba effect,spin hall effect,spin transfer torque
Projet ERC : PROTOEYE (Horizon 2020, appel 2020, Advanced grants)
Domaine scientifique : Life Science
Panel : Environmental Biology, Ecology and Evolution
Entité participante : University of Exeter — Pays : Royaume-Uni — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 132859.79 €

Complex animal eyes evolved many times independently from simpler forms. As already suggested by Darwin, the path to vision may have led from non-directional to directional light sensing and then to low-resolution spatial vision. Simple eyes in extant animals show a remarkable diversity of form and function and may hold the key to the origin of eyes and vision. We do not know why this diversity evolved when the organisms all respond to the same physical cue. Although we have a detailed molecular-centric view of eye evolution across animals, we lack corresponding knowledge of the physical mechanics and neuronal circuits coordinating the responses. PROTOEYE will study the diversity of simple non-visual and visual eyes and map the phase space of light-guided behaviours across animals. This will inform general principles of sensory system evolution and our understanding of the origin and evolution of eyes and visual circuits. The project will build on our long-term expertise in neural circuits and mechanistic photo-biology. We will study a range of aquatic invertebrates with distinct behavioural strategies, unified by the presence of simple eyes and non-visual photoreceptors. Instead of looking at eyes in isolation, we will investigate light responses from a whole-organism perspective focusing on circuits, behaviour and the biophysics of motion. In order to obtain entire neuronal circuits driving photic behaviours, we will use whole-body serial electron microscopy and connectomics. With laser ablation, we will explore strategies of light-seeking or light-avoidance behaviours. In high-throughput behavioural assays we will test navigation strategies and sensitivities to different wavelengths. With high-speed imaging and flow tracing, we will investigate how animal movement is shaped by light. This comparative and multi-disciplinary project will chart the functional diversity of simple eyes and provide a new framework for understanding the evolution of animal vision.

Mots-clés : eye evolution,neural circuits,marine larvae,light regulated behaviour,photoreceptors,microswimmers,biophysics,ciliated larvae,connectomics
Projet ERC : DeCoCt (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems Engineering
Entité participante : University of Tübingen — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1925500.0 €

Complex microbial communities ("microbiota") that populate surfaces of higher organisms critically impact health of their hosts: They contribute to vital functions such as host fitness, nutrient acquisition, stress tolerance and pathogen resistance but are, at the same time, reservoirs for facultative pathogens or can promote pathogenesis. How and why communities shift from a beneficial to a detrimental state is largely unknown and we are far from utilizing identified mechanisms. In order to cure detrimental microbiota, that were damaged or reverted through stress factors including previous diseases, decoding the complex processes governing microbiota dynamics is a key challenge. To develop durable probiotics, communal stability or the ability of a community to return to a steady state following perturbation is a key factor. Our lab has broad expertise in studying microbial communities through lab experiments and analyzing factors that shape the microbiota of Arabidopsis thaliana plants under natural conditions and common garden experiments. We have discovered a hierarchical order in microbial community networks with hub microbes as key elements. A recent breakthrough was the discovery of microbial taxa that persist throughout the life of A. thaliana plants and their importance in network stability. In this project we will use our expertise to identify key stability factors and drivers of communal dynamics to reconstitute synthetic communities. How to seed microbial communities that develop into functional probiotics is a key challenge. We will use knowledge based assembly of complex communities to seeds protective microbiota. We will challenge those through pathogens and abiotic factors to refine and test the predictive power of our analyses. Therefore, DeCoCt represents a highly innovative approach that holds the potential to gain novel insights beyond the current scope of microbiota and probiotics research.

Mots-clés : holobiont,synthetic microbial communities,microbiota
Projet ERC : resiliANT (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Life Science
Panel : Environmental Biology, Ecology and Evolution
Entité participante : University of Lausanne — Pays : Suisse — Rôle : PI
Acronyme de l'entité : UNIL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499969.0 €

Complex systems are found at all levels of biological organisation, from molecules to ecosystems. Despite the huge differences in scale, each of them has evolved homeostatic processes conferring resilience to external perturbations. Ants provide an ideal system to identify behavioural responses allowing biological systems to recover from disturbance. The overall aim of this proposal is to identify the collective mechanisms responsible for this resilience. This will be achieved by conducting both abiotic and biotic perturbations. Abiotic perturbations such as flooding frequently have major effects on the demography of the workforce, for example by whipping out all the foragers. We will therefore perform highly controlled perturbations (e.g., targeted removal of worker groups) designed to induce compensatory changes in the behavioural trajectories of the remaining ants to test whether ants can deviate from their baseline behavioural trajectory to mitigate the effect of external perturbations A major biotic challenge faced by all highly social species is the rapid spread of disease between closely-packed conspecifics. Because the kinetics of disease transmission in social groups depends upon the structure of the interaction network, we will investigate how the prophylactic properties of the social interaction network emerge from the individual-level behaviours. Finally, we will perform controlled inoculations with a generalist fungal pathogen to identify active individual-level behavioural responses that further hinder pathogen transmission. The proposed studies which capitalise on two recent methodological advancements (the development of sophisticated network analysis tools and, a tracking system which allows unprecedented collection of behavioural data (e.g., millions of pairwise interactions) will make important contributions to our understanding of processes involved in resilience of complex systems and how animal societies respond to stochastic environments.

Mots-clés : social behaviour,disease transmission,ants
Projet ERC : COLT-MDP (Horizon 2020, appel 2019, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Tel Aviv University — Pays : Israël — Rôle : PI
Acronyme de l'entité : TAU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1878125.0 €

Computational learning theory has been highly successful over the last three decades, both in providing deep mathematical theories and in influencing the practice of machine learning. One of the great recent successes of computational learning theory has been the study of online learning and multi-arm bandits. This line of research has been highly successful, both theoretically and practically, addressing many important applications. Unfortunately, the recent theoretical progress in Markov Decision Process and reinforcement learning has been slower. Based on my fundamental contributions to reinforcement learning (e.g. policy gradient, sparse sampling and trajectory trees), to online learning and machine learning in general, I propose to take the theoretical and practical success of online learning to the “next level” by making significant breakthroughs in reinforcement learning. Our main aim is to advance the state of the art in the theory of reinforcement learning, and our research will revolve around three pillars: (1) compact representation, (2) efficient computation and (3) societal challenges, including fairness and privacy. A successful project will greatly impact reinforcement learning in all its stages. Modelling: Introducing new compact representation models, will enhance our understanding how to structure complex problems, which would greatly extend the applicability of reinforcement learning. Efficient computation: New algorithmic methodologies will give new insight for overcoming computational and statistical barriers both for planning and learning. Learning: New learning paradigms would address fundamental issues of copping with uncertainties in complex control environments of reinforcement learning. Societal challenges: Allowing the community to understand, assess, address and overcome societal challenges is of the greatest importance to the acceptance of AI methodologies by the general public.

Mots-clés : online learning,reinforcement learning,computational learning theory,regret minimization,fairness,privacy
Projet ERC : CHAMELEON (Horizon 2020, appel 2015, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Universidad de Zaragoza — Pays : Espagne — Rôle : PI
Acronyme de l'entité : UNIZAR
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1629518.75 €

Computer-generated imagery is now ubiquitous in our society, spanning fields such as games and movies, architecture, engineering, or virtual prototyping, while also helping create novel ones such as computational materials. With the increase in computational power and the improvement of acquisition techniques, there has been a paradigm shift in the field towards data-driven techniques, which has yielded an unprecedented level of realism in visual appearance. Unfortunately, this leads to a series of problems, identified in this proposal: First, there is a disconnect between the mathematical representation of the data and any meaningful parameters that humans understand; the captured data is machine-friendly, but not human friendly. Second, the many different acquisition systems lead to heterogeneous formats and very large datasets. And third, real-world appearance functions are usually nonlinear and high-dimensional. As a result, visual appearance datasets are increasingly unfit to editing operations, which limits the creative process for scientists, engineers, artists and practitioners in general. There is an immense gap between the complexity, realism and richness of the captured data, and the flexibility to edit such data. We believe that the current research path leads to a fragmented space of isolated solutions, each tailored to a particular dataset and problem. We propose a research plan at the theoretical, algorithmic and application levels, putting the user at the core. We will learn key relevant appearance features in terms humans understand, from which intuitive, predictable editing spaces, algorithms, and workflows will be defined. In order to ensure usability and foster creativity, we will also extend our research to efficient simulation of visual appearance, exploiting the extra dimensionality of the captured datasets. Achieving our goals will finally enable us to reach the true potential of real-world captured datasets in many aspects of society.

Mots-clés : computer graphics,visual appearance,intuitive edits
Projet ERC : D-SynMA (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : University of Gothenburg — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1716274.5 €

Computing is changing from living on our desktops and in dedicated devices to being everywhere. In phones, sensors, appliances, and robots – computers (from now on devices) are everywhere and affecting all aspects of our lives. The techniques to make them safe and reliable are investigated and are starting to emerge and consolidate. However, these techniques enable devices to work in isolation or co-exist. We currently do not have techniques that enable development of real autonomous collaboration between devices. Such techniques will revolutionize all usage of devices and, as consequence, our lives. Manufacturing, supply chain, transportation, infrastructures, and earth- and space exploration would all transform using techniques that enable development of collaborating devices. When considering isolated (and co-existing) devices, reactive synthesis – automatic production of plans from high level specification – is emerging as a viable tool for the development of robots and reactive software. This is especially important in the context of safety-critical systems, where assurances are required and systems need to have guarantees on performance. The techniques that are developed today to support robust, assured, reliable, and adaptive devices rely on a major change in focus of reactive synthesis. The revolution of correct-by-construction systems from specifications is occurring and is being pushed forward. However, to take this approach forward to work also for real collaboration between devices the theoretical frameworks that will enable distributed synthesis are required. Such foundations will enable the correct-by-construction revolution to unleash its potential and allow a multiplicative increase of utility by cooperative computation. d-SynMA will take distributed synthesis to this new frontier by considering novel interaction and communication concepts that would create an adaptable framework of correct-by-construction application of collaborating devices.

Mots-clés : reactive synthesis,two player games,temporal logic