Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : SWING (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : University of Basel — Pays : Suisse — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1986430.0 €

Scattering of waves governs fundamental questions in science, from imaging molecules to fine-tuning concert hall acoustics. Efficient scattering computations rely on sparse representations of wavefields. Spurred by the empirical successes of deep learning, the emphasis has recently shifted to data-driven modeling. However, unlike signal-theoretic implementations that come with sharp approximation guarantees, it remains unclear whether the popular deep learning structures can represent important scattering operators. In SWING, we address this question by leveraging advances in signal processing and machine learning. We propose theory and algorithms for the upcoming, learning-based wave of breakthroughs in forward and inverse scattering. SWING is built on three research thrusts: 1. To design efficient computational structures with approximation guarantees for learning scattering operators. We will focus on minimal structures for Fourier integral operators which model key problems. 2. To treat learning for inverse scattering as a sampling problem and derive practical sample complexity results. We will explore connections between learning theory and stability of inverse problems, and examine the regularization roles of data, physics and nonlinearity. 3. To apply our techniques to two classes of inverse problems: (i) emerging modalities in molecular imaging, giving rise to problems in geometry and unlabeled sampling; and (ii) seismic tomography of Earth and Mars, with data-driven discretizations of scattering operators playing a central role. With the growth of wave-based sensing, there is an urgency to quantify the limits of the data-driven paradigm in scattering problems. The power of data in fitting models is indisputable: it is certainly the next frontier. We believe, however, that the best designs combine data-based models with an understanding of the underlying physics.

Mots-clés : wave equation,inverse problems,scattering,inverse scattering,machine learning,deep learning,multiple scattering,geophysics,seismic imaging,molecular imaging,cryoem,free electron laser,fourier integral operators,layer peeling,recurrent neural networks,diffeomorphisms
Projet ERC : CLAUSTROFUNCT (Horizon 2020, appel 2019, Synergy grants)
Entité participante : University of Geneva — Pays : Suisse — Rôle : CO-PI
Acronyme de l'entité : UNIGE
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 5000000.0 €

Schizophrenia is a chronic mental disease having an incidence of 1% worldwide. Its symptoms are numerous and range from hallucinations to altered executive functions. Although the exact causes of schizophrenia are unknown, several works suggest that impaired communication between higher cortical centers may be important for the expression of the disease. Establishing a causal link between circuit function (and/or dysfunction) and particular behavioral traits relevant to schizophrenia may shed new light on the mechanisms underlying the pathology. Dysfunction of the prefrontal cortex (PFC) may contribute to cognitive deficits relevant to schizophrenia. In a search for circuits potentially regulating the PFC, we identified an enigmatic and not well-studied network, the claustrum (CLA). This subcortical structure of unknown function is supposed to be highly reciprocally interconnected with the neocortex, especially associative cortices involved in behavioral traits relevant to schizophrenia. It is thus uniquely positioned to influence cortical communication. The CLA is also peculiar because it represents the brain structure expressing the highest levels of kappa opioid receptor, the receptor of the most potent hallucinogenic drug found in nature, salvinorin A, suggesting a potential role played by the CLA in hallucinations. This link is further supported by medical reports in which patients having transient or permanent lesions in the claustrum develop hallucinations and delusions concomitantly. Finally, many risk factors genes associated to schizophrenia are strongly and often selectively expressed in the mouse claustrum. In summary, this combination of evidences led us to hypothesize that the claustrum may represent a circuit whose malfunction is relevant to the expression of schizophrenia. Our proposal will test the role of the claustrum in the normal brain and test whether its dysfunction may contribute to schizophrenia symptoms.

Mots-clés : claustrum,ensemble coding,systems neuroscience,frontal cortex,mental disorder
Projet ERC : SCHIZTYPE (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Karolinska Institutet — Pays : Suède — Rôle : PI
Acronyme de l'entité : KI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2064414.0 €

Schizophrenia is a heritable but genetically complex disease. Pathological and epidemiological data fit a model of SCZ as a network disease with perturbations during brain development leading to early-adulthood onset clinical symptomatology. Our present understanding is based on single markers or arrays of gene expression from tissue samples containing multiple cell types. As a consequence, pathological changes in the function of inhibitory or excitatory neurons, microglia, or oligodendrocytes have variously been proposed to be the cause of symptoms. In light of recent data I hypothesize that it is unlikely that the various cellular SCZ-pathologies all arise independently from genetic alterations in multiple cell types. Recent findings from my lab show that in the cortex the expression of risk genes for SCZ are enriched in excitatory neurons, and that this set of risk-genes is largely non-overlapping with those expressed in other cell types. I propose that pathological genetic changes in excitatory cells ultimately initiates pathological changes in other cell types contributing to the multiple cellular pathologies observed in SCZ. We will: 1. Identify cell type-specific gene regulatory networks involved in SCZ (SCZ-GRNs) in prefrontal cortical excitatory cells by analysis of four distinct SCZ mouse models. 2. Confirm putative SCZ-GRNs in patient material using in situ transcriptomics on postmortem brains and connect to clinical features via collaboration with genomic studies in Sweden and Denmark. 3. Functionally investigate the effects of perturbing excitatory cell SCZ-GRNs on other cell types. Single-cell RNA-seq, providing insights into the molecular properties of individual cells, and modern molecular tools for perturbing transcription in a cell type-specific way opens up for new knowledge of mechanisms underlying SCZ pathology. My work will identify causal relationships that can be exploited for the development of strategies for personalized treatment.

Mots-clés : schizophrenia,human genetics,single cell sequencing,postmortem tissue,transcriptomics,mouse models
Projet ERC : CompSCHoice (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : Institute of political economy and governance — Pays : Espagne — Rôle : PI
Type d'entité : Recherche
Financement ERC de l'entité : 872923.21 €

School choice is one of the most hotly debated policies in education. Advocates argue that school choice allows equal access to high quality schooling for all. High-income families have always had more choice, either through residential choice or through enrolment in private schools. Therefore increased choice should also improve equity by allowing minority and low-income students to choose too. On the other hand, school choice critics suggest that school choice can increase sorting between schools based on their socio-economics status, suggesting high-income families benefit more from these policies. Three different and disconnected literatures in economics provide different and often contradicting answers to these questions. We propose a unified theoretical framework that merges these three literatures and allows for a comprehensive analysis on school choice design and its impact on actual choice, outcomes and segregation in schools and neighborhoods. Unique and newly constructed data sets are used to address novel empirical challenges. The data constructed for Barcelona shall become one of the largest and most comprehensive data sets not only on school choice but also on public education worldwide. Using the data set from Barcelona we 1) estimate families’ preferences and, for the first time, evaluate the efficiency of different mechanism through structural estimation of our model and counterfactual analysis. We then 2) evaluate the impact that peer effects have on parents' choice and on outcomes. Exploiting the occurrence of hurricane Katrina in New Orleans and the aid programs implemented we aim at 3) estimating the distribution of willingness to pay for quality schools for families with different socio-economics. And last we exploit a policy change in Catalunya in 2009 to 4) provide evidence on how increased flexibility of the school system to adapt for differential maturity levels affects individual short and medium-term outcomes.
Projet ERC : NanoBubbles (Horizon 2020, appel 2020, Synergy grants)
Entité participante : École nationale des ponts et chaussées — Pays : France — Rôle : Partner
Acronyme de l'entité : ENPC
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 152896.25 €

Science relies on the correction of errors to advance, yet in practice scientists find it difficult to erase erroneous and exaggerated claims from the scientific record. Recent discussion of a “replication crisis” has impaired trust in science both among scientists and non-scientists; yet we know little about how non-replicated or even fraudulent claims can be removed from the scientific record. This project combines approaches from the natural, engineering, and social sciences and the humanities (Science and Technology Studies) to understand how error correction in science works and what obstacles it faces, and stages events for scientists to reflect on error and overpromising. The project’s focus is nanobiology, a highly interdisciplinary field founded around the year 2000 that has already seen multiple episodes of overpromising and promotion of erroneous claims. We examine three such “bubbles”: the claim that nanoparticles can cross the blood-brain barrier; that nanoparticles can penetrate the cell membrane; and the promotion of the “protein corona” concept to describe ordinary adsorption of proteins on nanoparticles. Findings based on error (non)correction in nanobiology should be generalizable to other new, highly interdisciplinary fields such as synthetic biology and artificial intelligence. We trace claims and corrections in various channels of scientific communication (journals, social media, advertisements, conference programs, etc.) via innovative digital methods. We examine error (non)correction practices in scientific conferences via ethnographic participant-observation. We follow the history of conferences, journals, and other sites of error (non)correction from the 1970s (before nanobio per se existed) to the present. And we attempt to replicate nanobiological claims and, in case of non-replication, document obstacles to correcting those claims. Finally, we will spark a dialogue within the nanobiology community by organizing workshops and events at c

Mots-clés : conference studies,scientometrics,controversy studies,sociology of science,scientific publishing,cell imaging,blood brain barrier,endocytosis,text mining,post publication peer review
Projet ERC : FINDER (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The study of the human past
Entité participante : University of Vienna — Pays : Autriche — Rôle : PI
Acronyme de l'entité : Univie
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 901262.5 €

Scientific analyses of ancient biomolecules (proteins, DNA, hard tissues) have transformed our knowledge of archaic hominins present in Eurasia prior to the expansion of modern humans from Africa. In 2010, a finger bone discovered in Siberia was assigned using DNA to a new, previously unknown human group, the Denisovans. The Denisovans interbred with both Asian Neanderthals and AMH over the past 100,000 years; their geographic distribution is now thought to have stretched from the Siberian steppes to the tropical forests of SE Asia and Oceania. Despite their broad spatio-temporal range, the Denisovans are only known from 4 tiny bones, all from a single Siberian cave. This patchy knowledge of an entire human population significantly limits our ability to test hypotheses and interpretative models concerning major issues in human evolution, such as the routes and timing of people movements across Asia, the nature and frequency of interaction between archaic indigenous groups and migratory modern humans, the mechanisms leading to the demise of archaic lineages and eventual sole dominance of our species on Earth. This project aims to rectify the dearth of Denisovan fossils by applying a novel combination of cutting-edge scientific methods (collagen fingerprinting, radiocarbon dating and ancient DNA analyses) designed to identify, date and genetically characterize new human fossils, with a particular emphasis on the discovery of Denisovan remains. Instead of only focusing on the few morphologically identifiable human bones, a groundbreaking high-throughput approach will target bulk collections of unidentified bone fragments (n=30,000) from ~20 Asian sites dating to between 100,000-10,000 years. Ultimately, the goal is to expand our understanding of the Denisovans, reveal their geographic range, age, genetic variation and archaeological signature. In addition to solving the puzzles of ancient population history, this research has the potential to decode the patchwork that makes modern humans who we are today, physically, behaviourally and genetically.

Mots-clés : denisovans,palaeolithic,neanderthals,homo sapiens,archaeological science,radiocarbon dating,ancient dna,collagen fingerprinting
Projet ERC : mR-NIPD (Horizon 2020, appel 2015, Proof of concept grants)
Entité participante : Nipd genetics public company limited — Pays : Chypre — Rôle : PI
Type d'entité : Organismes privés (hors enseignement)
Financement ERC de l'entité : 150000.0 €

Scientific and medical evidence indicate that non-invasive prenatal testing, known as non-invasive prenatal testing (NIPT), is a safer alternative to invasive tests that might put the pregnancy at risk. Modern NIPT examine traces of fetal DNA in the maternal bloodstream to determine whether the fetus is at risk of chromosomal abnormalities such as, but not limited to, Down syndrome (trisomy 21), Patau syndrome (trisomy 13) and Edward’s syndrome (trisomy 18). In this ERC Proof of Concept Grant (mR-NIPD), we anticipate to correlate already discovered DNA biomarkers of the ERC NIPD (funded ERC) with biomarkers in mRNA transcripts. The method, directly related to the currently funded ERC, will use m6A-specific methylated mRNA immunoprecipitation combined with Next Generation Sequencing (MeRIP-Seq) on fetal and maternal mRNA samples. As a result, we aim to increase the number of fetal specific biomarkers and provide a novel, cost-effective non-invasive prenatal test that will be accessible to all pregnant women independent from social and economic status

Mots-clés : nipd,mr nipd,cell free rna,down syndrome,fetal epigenetic biomarkers,next generation sequencing,differentially methylated regions
Projet ERC : BOLD (Horizon 2020, appel 2020, Synergy grants)
Entité participante : University of Valencia — Pays : Espagne — Rôle : PI
Acronyme de l'entité : UV
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Searching for neutrinoless double beta decays (NLDBD) is the only practical way to establish if the neutrinos are their own antiparticles, a discovery of enormous importance for particle physics and cosmology. Due to the smallness of neutrino masses, the lifetime of NLDBD is expected to be much longer than the ones from the noise associated with the natural radioactive chains. A positive identification of NLDBD decays requires finding a signal that cannot be mimicked by radioactive backgrounds. In particular, the NLDBD decay of Xe-136 could be established by detecting the doubly ionized daughter atom, Ba2+ created in the decay. Such a detection could be achieved via a sensor made of a monolayer of molecular indicators. The Ba2+ would be captured by one of the molecules in the sensor, and the presence of the single Ba2+-complexed indicator would be subsequently revealed by a fluorescent response after interrogation with a laser system. Our proposed sensor is based on a new type of molecular bicolor fluorescent indicators, able to shift their emission spectra when complexed with Ba2+. The interrogation and detection system will be based in fast, two photon absorption microscopy. The primary goals of this proposal are: 1, a full demonstration of the feasibility of a sensor capable of detecting single Ba2+ ions in a High Pressure Xenon Chamber (HPXe), and 2) the construction of a large HPXe demonstrator, the BOLD detector, which will implement a full Barium Tagging Detector System and will demonstrate the feasibility of building a background-free experiment at the ton-scale, with large discovery potential.

Mots-clés : neutrinoless double beta decay,supramolecular chemistry,barium tagging,lasers,ion beams,sensors,particle physics,instrumentation
Projet ERC : NaviFlu (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Life Science
Panel : Environmental Biology, Ecology and Evolution
Entité participante : Amsterdam University Medical Centers — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999331.0 €

Seasonal influenza viruses re-infect us repeatedly, escaping antibody recognition, due to the evolution of the virus itself. Being able to predict when and how the virus will evolve would be transformative for influenza virus control. Problematically, we have only observed one of the likely many possible routes of virus evolution. We do not know how many viable routes may have existed or about the repeatability of the observed evolution. These knowledge gaps limit the predictability of influenza virus evolution. NaviFlu will fill these gaps by rigorously assessing the repeatability of influenza virus evolution and the diversity of routes the virus can explore. Recent work has shown that prolonged influenza virus infections can result in substantial virus evolution and occasionally portend virus mutational patterns on a global scale. However, observing large numbers of such infections is challenging. We will use an innovative ex-vivo human airway epithelium culture system to artificially create and study prolonged human infections. Together with cutting-edge next generation sequencing and new analysis tools, we will quantify the evolutionary landscape of seasonal influenza viruses. The project has three objectives, each building in complexity: 1–Quantify the evolutionary dynamics of seasonal influenza viruses in the absence of antibody-mediated selection. 2–Determine how the antibody complexity of immune sera shape the evolutionary trajectories of virus antigenic evolution. 3–Quantify the impact of differences in selection pressures by site of infection and underlying host variation on virus evolution. Through these objectives we will “play evolution forwards”, revealing the relative roles of different factors governing the mode and tempo of influenza virus evolution and quantify the predictability of virus evolution. This will improve the design of influenza vaccines, enhance prospects for influenza control, and lay new groundwork for exploring virus evolution.

Mots-clés : influenza viruses,evolutionary fitness landscapes,long term evolution,experimental evolution
Projet ERC : NTSC (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Technion – Israel Institute of Technology — Pays : Israël — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1546758.0 €

Secure computation is a general-purpose tool for processing sensitive data without compromising its confidentiality or integrity. In recent years, significant research efforts have been invested in optimizing and implementing secure computation protocols and related cryptographic primitives such as fully homomorphic encryption and program obfuscation. The proposed project will explore new techniques for secure computation and related primitives. The new techniques are expected to enhance the asymptotic and concrete efficiency of current solutions and extend the known relations between secure computation and other problems in cryptography and computational complexity theory. The research will span the following directions: • Succinct secure computation via homomorphic secret sharing, exploring new research directions that were opened by recent works of the PI; • Protecting protocols against malicious parties, with relevance to efficient general-purpose program obfuscation; • Protecting protocols against general information leakage

Mots-clés : secure multiparty computation,computational complexity theory