Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : StuDySARCOMERE (Horizon 2020, appel 2019, Synergy grants)
Entité participante : University of London — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : U. London
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499190.0 €

Muscles are specialized tissues that power voluntary, fast and coordinated movements, a hallmark of animal life. The force-generating and load-bearing devices of muscles are called sarcomeres, highly structured ensembles of many proteins. While many sub-components are structurally and functionally characterised, muscle is more than the sum of these parts: its function is highly cooperative and its structure dynamic over time and space. The high-resolution structure of sarcomeres is unknown, yet a precise molecular understanding of how the entire sarcomere machine forms and functions is required to understand its role in health, disease and ageing. This consortium will deploy an unparalleled complementary knowledge and technology base to address these fundamental and translational questions. We will solve the structure of the sarcomere at near-atomic resolution, uMuscles are specialized tissues that power voluntary, fast and coordinated movements, a hallmark of animal life. The force-generating and load-bearing devices of muscles are called sarcomeres, highly structured ensembles of many proteins. While many sub-components are structurally and functionally characterised, muscle is more than the sum of these parts: its function is highly cooperative and its structure dynamic over time and space. The high-resolution structure of sarcomeres is unknown, yet a precise molecular understanding of how the entire sarcomere machine forms and functions is required to understand its role in health, disease and ageing. This consortium will deploy an unparalleled complementary knowledge and technology base to address these fundamental and translational questions. We will solve the structure of the sarcomere at near-atomic resolution, unravel the fundamentals of its force-driven assembly and turnover in health and ageing, and develop the foundations for future basic and translational research including the design and development of new agents to mitigate muscle disease and ageing.

Mots-clés : muscle,sarcomere,structure,electron cryo tomography,nanobodies,myofibrils,nanostructure,actin,myosin,obscurin,ageing,titin,super resolution microscopy,genome editing,myofibrillogenesis,self organization
Projet ERC : PMSB (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
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 : 1500000.0 €

Music is a central human trait across all cultures and historical periods, involving a great rich variety of parameters, cognitive processes, and forms of structure building. The proposed project aims at advancing the understanding of human cognition and, specifically, the capacity to represent and process complex auditory sequences and syntactic structures by exploring the rich potential of music perception. Building on the PI’s previous work, this interdisciplinary research programme will be divided into three core strands: (A) The theoretical strand will be devoted to the investigation of formal principles that govern musical syntax and structure building in Western and non-Western music. Many current approaches share the expressive power of (tree-based) context-free grammars and are mostly confined to harmonic syntax only. Therefore, they face difficulty in expressing certain crucial syntactic phenomena in music. To address this lacuna, the theoretical strand will develop a novel unified theory of musical syntax that exceeds context-free complexity and reconciles harmonic structure with the constraints of voice leading within a single coherent framework. (B) Addressing the lack of machine-readable corpora in music research, a large corpus of digitized syntactic analyses will be compiled and published in the context of the project’s computational strand. Further, the unified syntax theory will be implemented based on a generalized parsing approach and graph grammars, and trained and evaluated using the analytical corpus. (C) The formal framework developed in (A) entails specific predictions about mental representations of musical structure that will be empirically tested in the experimental strand of the project. Particular focus will be on aspects of nonlocal dependency relations, learnability, revision, and tension. The outcomes of the project will make a significant contribution to both the field of music cognition and to the cognitive sciences in general.

Mots-clés : music cognition,syntax,corpus analysis,hierarchical processing,recursion,cross cultural analysis
Projet ERC : COSMOS (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Cultures and cultural production
Entité participante : University of London — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : U. London
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1510721.47 €

Music performance is considered by many to be one of the most breath taking feats of human intelligence. That music performance is a creative act is no longer a disputed fact, but the very nature of this creative work remains illusive. Taking the view that the creative work of performance is the making and shaping of music structures, and that this creative thinking is a form of problem solving, COSMOS proposes an integrated programme of research to transform our understanding of the human experience of performed music, which is almost all music that we hear, and of the creativity of music performance, which addresses how music is made. The research themes are as follows: i) to find new ways to represent, explore, and talk about performance; ii) to harness volunteer thinking (citizen science) for music performance research by focussing on structures experienced and problem solving; iii) to create sandbox environments to experiment with making performed structures; iv) to create theoretical frameworks to discover the reasoning behind the structures perceived and made; and, v) to foster community engagement by training experts to provide feedback on structure solutions so as to increase public understanding of the creative work in music performance. Analysis of the perceived and designed structures will be based on a novel duality paradigm that turns conventional computational music structure analysis on its head to reverse engineer why a perceiver or a performer chooses a particular structure. Embedded in the approach is the use of computational thinking to optimise representations and theories to ensure accuracy, robustness, efficiency, and scalability. The PI is an established performer and a leading authority in music representation, music information research, and music perception and cognition. The project will have far reaching impact, reconfiguring expert and public views of music performance and time-varying music-like sequences such as cardiac arrhythmia.

Mots-clés : music performance studies,music perception and cognition
Projet ERC : COSMOS (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Cultures and cultural production
Entité participante : University of London — Pays : Royaume-Uni — Rôle : Partner
Acronyme de l'entité : U. London
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 0.0 €

Music performance is considered by many to be one of the most breath taking feats of human intelligence. That music performance is a creative act is no longer a disputed fact, but the very nature of this creative work remains illusive. Taking the view that the creative work of performance is the making and shaping of music structures, and that this creative thinking is a form of problem solving, COSMOS proposes an integrated programme of research to transform our understanding of the human experience of performed music, which is almost all music that we hear, and of the creativity of music performance, which addresses how music is made. The research themes are as follows: i) to find new ways to represent, explore, and talk about performance; ii) to harness volunteer thinking (citizen science) for music performance research by focussing on structures experienced and problem solving; iii) to create sandbox environments to experiment with making performed structures; iv) to create theoretical frameworks to discover the reasoning behind the structures perceived and made; and, v) to foster community engagement by training experts to provide feedback on structure solutions so as to increase public understanding of the creative work in music performance. Analysis of the perceived and designed structures will be based on a novel duality paradigm that turns conventional computational music structure analysis on its head to reverse engineer why a perceiver or a performer chooses a particular structure. Embedded in the approach is the use of computational thinking to optimise representations and theories to ensure accuracy, robustness, efficiency, and scalability. The PI is an established performer and a leading authority in music representation, music information research, and music perception and cognition. The project will have far reaching impact, reconfiguring expert and public views of music performance and time-varying music-like sequences such as cardiac arrhythmia.

Mots-clés : music performance studies,music perception and cognition
Projet ERC : EScORIAL (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : University Medical Center Utrecht — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : UMC
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1980434.0 €

My aim is to understand the exact genetic contribution in every patient with Amyotrophic Lateral Sclerosis (ALS), a lethal disease with a life time risk of 0.3% and an urgent unmet therapeutic need. I have recently shown a disproportionate large contribution from low-frequency genetic variants in ALS. ALS is not simply a collection of unique rare diseases with a monogenetic cause nor is it a diagnostic continuum with a complex contribution of thousands of small effect factors. ALS is in-between, which I call “simplex”, where in each patient a few, considerably strong genetic factors with or without environmental factors are at play. ALS mutations are characterized by reduced penetrance, variable clinical expressivity, have specific pleiotropic clinical features and interact with environmental factors. These phenomena are unexplained, but provide me with important and new opportunities in order to unravel the clinical, genetic and biological heterogeneity in ALS. I have created new research fields to go an important step beyond the state of the art: Splitting by lumping uses novel machine learning algorithms to reclassify patients using clinical pleiotropic features, environmental factors and blood epigenetic profiles to identify novel ALS mutations. Imaging genomics overlays patterns in ALS-associated brain morphology on MRI with brain gene-expression patterns to find ALS mutations. ALS risk in 3D integrates data on three-dimensional folding of DNA with genetic data to identify causal mutations and mutation-to-mutation interaction. ALS genomic modifiers in 3D identifies modifiers of C9orf72 mutations through the development of cellular reporter assays and CRISPR-Cas9 based screens. Genomic findings are translated using cellular models which can be used for targeted and unbiased drug screens. If successful, my approaches can be applied beyond the scope of this ERC and will have a clear impact on clinical trial design and genetic counselling in ALS in particular.
Projet ERC : SubNano (Horizon 2020, appel 2018, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : Aix-Marseille Université — Pays : France — Rôle : PI
Acronyme de l'entité : amU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2498937.5 €

My goal in the SubNano project is to massively speed up the dynamics simulation of photoexcited molecules to allow addressing sub-nanosecond phenomena (that is, one thousand times above the current limits). The sub-ns methodology will be employed to investigate the long timescale nonadiabatic dynamics of photoinduced processes in nucleic acids, including DNA photostabilization via excitonic processes, biological fluorescent markers, and transient anion formation in DNA repair. To fulfill these goals, I will develop and implement a series of methods to extend nonadiabatic dynamics simulations into the new timescale, mainly based on a novel adaptive diabatic machine learning algorithm and a novel zero-point-corrected and vibronically-corrected mixed quantum-classical method. The sub-ns methodology will be constrained to be general (any kind or size of molecule), black-box (minimum user intervention), modular (adaptable to any electronic structure theory), on-the-fly (no need of precomputed potential energy surfaces), and local (independent-trajectories). It will be implemented into the Newton-X software platform, which I have been the main designer and developer. It will also be made available for all academic community through new releases of Newton-X. For the last 25 years, theoretical investigations of photodynamical processes have been restricted to the ultrafast (picosecond) regime, selectively choosing problems in this domain. The extension into the sub-ns regime is finally feasible thanks to a large algorithmic infrastructure I have built over the last 13 years, paving the grounds to develop a new research area, atomistic nonadiabatic dynamics on the long timescale. The success of the SubNano project will have an enormous impact on the research field, allowing to investigate outstanding interdisciplinary phenomena in chemistry, biology, and technology, which have been neglected due to a lack of methods.

Mots-clés : nonadiabatic dynamics,photophysics,mixed quantum classical methods
Projet ERC : QINTERNET (Horizon 2020, appel 2015, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Delft University of Technology — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : TU Delft
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1498725.0 €

My goal is to overcome the two-most pressing theoretical challenges necessary to build large-scale quantum communication networks: routing and designing protocols that use them to solve useful tasks. In two interconnected projects, I will devise entirely new concepts, models and mathematical methods that take into account the intricacies of real world quantum devices that can operate on only very few quantum bits at a time. (1) Security: I will prove the security of quantum cryptographic protocols under realistic conditions, and implement them in collaboration with experimentalists. I will develop a general theory and practical tests for the security of multi-party cryptographic primitives using untrusted quantum devices. This is mathematically challenging due to the possibility of entanglement between the devices. (2) Routing: I will initiate the systematic study of effective routing in a quantum communication network. This is necessary for quantum networks to grow in scale. Quantum entanglement offers very different means of routing messages than is possible in classical networks, and poses genuinely new challenges to computer science. I will design routing protocols in a multi-node quantum network of potentially different physical implementations, i.e., hybrid networks, that will establish a new line of research in my field. Quantum networks are still in their infancy, even though quantum communication offers unparalleled advantages that are provably impossible using classical communication. Building a quantum network is an interdisciplinary effort bringing together computer science, physics, and engineering. I am in a unique position in computer science, since I have recently joined QuTech where I have direct access to small quantum devices - bringing me tantalizingly close to seeing such networks realized. As with early classical networks, it is difficult to predict where our journey will end, but my research will join theory and experiment to move forward.

Mots-clés : quantum information theory,quantum cryptography,quantum repeater
Projet ERC : Merlin (Horizon 2020, appel 2019, Advanced grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : University of Geneva — Pays : Suisse — Rôle : PI
Acronyme de l'entité : UNIGE
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499337.5 €

My group aims at fostering the regeneration of insulin-producing β-cells in the diabetic pancreas by promoting the reprogramming of other islet endocrine “non-β” cells. I will use mice and human islets to trigger the metabolic reprogramming of: i) peripheral organs, in order to reduce hyperglycemia, and ii) human islet non-β-cells, to induce their acquisition of insulin secretion. I developed transgenics to elicit total (>99%) or graded (5-90%) β-cell loss. These mice revealed that non-β-cells, which produce other hormones, can naturally switch to insulin production upon β-cell loss, and lead to diabetes recovery. My group recently showed that human non-β-cells, from healthy or diabetic donors, also display plasticity and can engage in regulated insulin secretion. What metabolic adaptations occur in peripheral organs in response to insulin deficiency, but without complications? Can metabolic reprogramming of peripheral organs, based on these adaptations, suffice to control glycemia? Can metabolic reprogramming change the identity of a cell? Natural recovery of euglycemia after β-cell loss is documented in mice. To know the mechanisms driving relief, my lab will characterize islet cell dynamics and circulating molecules (metabolites, RNA, peptides) after various degrees of β-cell loss. We will perform a full analysis of blood and peripheral organs in recovered mice, and an array of genetic and pharmacological experiments modulating BAT mass and function to test its role in taming hyperglycemia. We will explore and define the metabolic differences between human β- and non-β-cells. Using monotypic “pseudoislets” we will do RNAseq, proteomics and metabolomics after exposure to glucose. We will quantify oxygen consumption, extracellular acidification and ATP production in response to nutrients and metabolic toxins. From this, we will genetically (CRIPR-Cas9) and chemically reprogram the metabolism of human non-β-cells to boost the expression of β-like genes.

Mots-clés : diabetes,regeneration,cell plasticity,cell reprogramming,metabolic reprogramming,insulin deficiency,cell type interconversion,non beta cells,human islet,pseudo islet,transgenic
Projet ERC : MapItAll (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe sciences
Entité participante : University of London — Pays : Royaume-Uni — Rôle : Partner
Acronyme de l'entité : U. London
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 221423.29 €

My proposal is to map out the 3D structure of the Universe over an unprecedentedly broad swath of cosmic time, covering 13 billion years of cosmic history. I will do this by using radio telescopes to detect the 21cm emission from neutral hydrogen. The detailed statistical properties of the maps will allow us to answer some of the most pressing questions in cosmology, such as how fast space is expanding, what the physical properties of dark energy are, and how the first stars and galaxies lit up the Universe. All experiments currently trying to make these observations are severely limited by systematic effects, exacerbated by the extremely high dynamic range between the cosmological signal and many other sources of radio emission. Even tiny calibration errors can cause huge artefacts in the data that make it extremely difficult to pick out the target signal. While a great deal of work has gone into designing methods to analyse the data, they are not yet accurate enough – by a factor of 100 by some measures. I will develop a statistical analysis framework called “Total Calibration” that can deliver the remaining two orders of magnitude of improvement, and apply it to the most sensitive data available. The result will be precise, systematics-free maps and the most robust statistical measurements of large-scale structure ever made in the radio. Total Calibration seeks to model all of the relevant degrees of freedom in the data simultaneously, in one large global model of the signal, contaminants, and the calibration of the telescope. This is highly complex, and has never been done before. By applying total calibration to sensitive but complex data from two cutting-edge telescopes, HERA and MeerKAT, I will obtain the most robust constraints on the 21cm signal to date, from redshifts 0–1.4 (late times) and 5–27 (reionisation/Cosmic Dawn), to constrain the physical processes that shaped the cosmic energy budget at high redshift and any possible evolution of dark energy.

Mots-clés : reionization,intensity mapping,neutral hydrogen,astrostatistics,observational cosmology
Projet ERC : MtbTransReg (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
Entité participante : University of London — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : U. London
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1495625.0 €

Mycobacterium tuberculosis causes human tuberculosis but can also persist for decades as an asymptomatic latent infection. The mechanisms underlying persistence are poorly understood, and the emergence of drug-resistant tuberculosis makes the development of effective new treatments an urgent challenge. Understanding the ability of M. tuberculosis to switch between replicating and non-replicating states during infection and disease is central to the search for improved treatments. The number of copies of a protein produced by a cell is generally viewed as being determined by the number of mRNA transcripts, but recent findings suggest that ‘specialised ribosomes’ can modify proteome profiles by preferential translation of particular mRNA subsets, particularly in response to stress. mRNA molecules contain specific signals that optimise their interaction with ribosomes; known as leader sequences, these include the Shine-Dalgarno (SD) sequence required for canonical translation initiation in bacteria. I recently demonstrated that M. tuberculosis expresses an unexpected number of leaderless mRNA transcripts that lack the SD sequence. In Escherichia coli, only a few leaderless transcripts have been described and they are selectively translated by specialised ribosomes. I propose to test the hypothesis that differential translation of mRNA subsets contributes to M. tuberculosis persistence and drug susceptibility. I will investigate the importance of selective translation of leaderless and SD mRNAs in the context of adaptation to stress and drug resistance in M. tuberculosis, using cutting-edge experimental techniques combined with bioinformatic analyses. The proposed project addresses the fundamental systems biology challenge of establishing quantitative correlations between transcriptome and proteome data, and beyond contributing to the rational design of novel treatments to cure tuberculosis, could help to re-shape classical paradigms of bacterial gene regulation.