Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : TAILOMET (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : Université de Constance — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499868.0 €

TAILOMET will explore and exploit the hidden magic methyl effect in nature to develop genetically programmable biocatalytic systems for the production of tailor-made terpenoids. Given the immense pharmaceutical and industrial importance of terpene natural products, methodologies for strategic structure modifications to fine-tune physicochemical properties are of vast interest. Introduction of a single methyl group can have dramatic impact on a drug lead’s potency, selectivity, or pharmacokinetics, and can alter olfactory reception of aroma compounds. The influence of methylations on the bioactivity of terpenes has, however, never been systematically investigated due to the limited availability of suitable methodologies to introduce such structural modifications into terpene scaffolds. Our recent discovery on a novel general pathway to homoterpenes, together with bioinformatic analyses indicates widespread interkingdom occurrence of terpene C-methylations in nature. The findings suggest a readily available and vast treasure trove for the discovery of novel enzymology to develop biocatalytic systems for selective methyl installation into terpene backbones. By exploration, exploitation, and re-design of these naturally available enzymes, TAILOMET will develop a comprehensive toolbox to close current knowledge gaps and unlock rapid access to terpenoids with fine-tuned or even novel properties. Besides synthetic advancements, comprehensive insights into the biological function of terpene methylations in nature might shed novel lights on intra- and interspecies communication with potentially valuable implications for chemical ecology and natural product discovery.

Mots-clés : natural products,enzyme discovery,biosynthesis,biocatalysis,terpenes,methyltransferases
Projet ERC : GREEKWEST (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Study of the Human Past
Entité participante : Université de Liverpool — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1440137.0 €

This project reconstructs the place of Greek in the sociolinguistic landscape of western Europe during Late Antiquity (300–700 CE). Integrating textual and epigraphic evidence, it will trace the evolving use and knowledge of Greek in literary and political culture, religion, and daily life. This period witnessed transformations that would change the shape of European history: the rise of Christianity, the fragmentation of the western Roman empire, the introduction of new political and economic institutions, and the resulting restructuring of civic society. Views on the place of Greek in the late antique West still centre around deterministic narratives of ‘decline and fall’, leading to instances of Greek knowledge being dismissed as outliers, thus missing opportunities to examine the period’s continuing cultural, political, and linguistic interactions between ‘East’ and ‘West’. Challenging this consensus, GREEKWEST is ground-breaking in that it is the first study to examine Greek’s changing role in the late antique West and to do so across multiple social contexts. Spoken by roughly half the empire’s inhabitants, Greek had long occupied a central role in Roman society. On the one hand, Greek was seen as a language of high culture and prestige, and educated elite Romans were expected to be bilingual in Latin and Greek. At the same time, Greek was often associated with people from less privileged parts of society: slaves, performers, and merchants. This project seeks a) to establish who knew and used Greek in the late antique West and what sectors of society they came from, b) to reconstruct the motivations for using and learning Greek, and c) to trace how individuals and communities in the West learned and accessed Greek knowledge. This research will fundamentally change our understanding of the social history of language and migration, late antique intellectual and political culture, and the paradigms by which we view the transformations of the Roman world.

Mots-clés : late antiquity epigraphy bilingualism and sociolinguistics
Projet ERC : ixAutoML (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Université Gottfried-Wilhelm-Leibniz de Hanovre — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1459763.0 €

Trust and interactivity are key factors in the future development and use of automated machine learning (AutoML), supporting developers and researchers in determining powerful task-specific machine learning pipelines, including pre-processing, predictive algorithm, their hyperparameters and--if applicable--the architecture design of deep neural networks. Although AutoML is ready for its prime time after it achieved impressive results in several machine learning (ML) applications and its efficiency improved by several orders of magnitudes in recent years, democratization of machine learning via AutoML is still not achieved. In contrast to previously purely automation-centered approaches, ixAutoML is designed with human users at its heart in several stages. First of all, the foundation of trustful use of AutoML will be based on explanations of its results and processes. Therefore, we aim for:  1. Explaining static effects of design decisions in ML pipelines optimized by state-of-the-art AutoML systems. 2. Explaining dynamic AutoML policies for temporal aspects of dynamically adapted hyperparameters while ML models are trained.  These explanations will be the base for allowing interactions, bringing the best of two worlds together: human intuition and generalization capabilities for complex systems, and efficiency of systematic optimization approaches for AutoML. Concretely, we aim for:  3. Enabling interactions between humans and AutoML by taking human's latent knowledge into account and learning when to interact. 4. Building first ixAutoML prototypes and showing its efficiency in the context of Industry 4.0.  Perfectly aligned with the EU's AI strategy and recent efforts on interpretability in the ML community, we strongly believe that this timely human-centered ixAutoML will have a substantial impact on the democratization of machine learning.

Mots-clés : automated machine learning,interpretability,human centered ai
Projet ERC : REASONS F1RST (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Compl exity
Entité participante : Université de Bielefeld — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1449115.0 €

Some of the core fields of philosophy – including moral philosophy, value theory, and epistemology – are, at their heart, concerned with normative questions: questions about what is good or bad, right or wrong, justified or unjustified. These questions concern the content of judgements that human beings are constantly making and that structure our way of thinking, feeling, and acting. But while there is wide agreement in contemporary philosophy that normative judgements form a unified and important category of human thought, philosophers still struggle to understand what normativity actually is. One highly attractive hypothesis is that normativity can be analysed in terms of reasons – i.e. in terms of the factors that count in favour of or against actions or attitudes. But the systematic exploration of this Reasons-First Approach is still lacking. REASONS F1RST aims to undertake this much-needed investigation. Fostering multidisciplinary conversations, the project will explore the Reasons-First Approach on a large scale. It seeks to address recent challenges to the Reasons-First Approach and to show that it prevails over alternative approaches to understanding normativity. REASONS F1RST thus pursues a twofold objective: (i) to assess the merits and demerits of the Reasons-First Approach compared to alternative proposals and (ii) to work out in detail how different normative phenomena – including values, obligations and rights, the justification of beliefs, as well as appropriateness norms for emotions – can be explained in terms of reasons. Building on the work of a multidisciplinary research team, REASONS F1RST aims at nothing less than a fundamental understanding of one of the most important concepts of contemporary philosophy.

Mots-clés : analytic philosophy,conceptual analysis,normativity,meta ethics,meta normativity,meta epistemology,epistemology,moral philosophy,ethical theory,value theory,philosophy of mind,philosophy of language,philosophy of emotions
Projet ERC : DEEPFUNC (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Compl exity
Entité participante : Université Justus-Liebig de Gießen — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1494750.0 €

Over the last few decades, neuroscientists have identified multiple brain regions that perform distinct, often highly specialized functions such as processing faces, understanding language, and even thinking about what other people are thinking. Despite our increased understanding of the computations performed in these regions, the precise causes and origins of functional specialization in the brain are still a mystery and not accessible to direct experimental approaches.  Here, we propose to combine cutting-edge computational modelling, large-scale sampling of naturalistic behaviour and human neuroimaging to overcome these limitations. Focusing on visual perception, we will exploit the latest advances in artificial neural networks to probe three critical aspects of functional specialization in the ventral visual pathway: First, by training networks on natural and artificial visual categories and identifying which features result in functional specialization, we will characterize what it is about a visual category that leads to functional specialization. Second, we will leverage large-scale egocentric datasets of infant and adult visual input to test how visual experience and natural input statistics shape functional specialization during development. Third, we will ask why certain neural features become specialized for high-level visual categories in the human visual cortex in the first place. Critically, for each of these aspects, we will close the loop and directly test and validate its predictions in the human brain.  Our project will shed light on functional specialization from a new angle – by relating functional specialization to the computational constraints of performing tasks in the real world. Using this novel approach, our project tackles some of the most fundamental questions about the functional organization of the human mind and brain – the what, how and why of functional specialization.

Mots-clés : functional specialization,deep neural networks,fmri,eeg,ventral visual pathway,natural vision,face perception,task optimization
Projet ERC : NoOne (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and Processes Engineering
Entité participante : Université de Bari — Pays : Italie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1969012.75 €

Biomarkers are measurable indicators of a particular disease state of an organism. There has been an increasing demand for diagnostic markers, enabling reliable and non-invasive screening of peripheral biofluids. It is also established that a universal screening against life-threatening diseases, such as cancer, or infectious disease outbreaks, can be accomplished only by combining genomic and protein marker-based tests. The NoOne project aims at conceiving, engineering, fabricating and validating a ground-breaking platform based on a single-molecule binary bioelectronic sensor, capable to reliably discriminate biofluid samples enclosing zero biomarkers from those containing just one. The technology can be used for ultimate binary sensing of both proteins/peptides and genomic markers to enable the reliable screening of diseases such as cancer as well as viral and bacterial infections. The NoOne binary platform is designed to be portable, cost-effective, easy to operate and with a time-to-results within one hour; hence it is the ideal candidate for point-of-care applications. The prototype will enable clinicians, phytopathologists or veterinaries, to identify the set of samples that are totally free from a protein, peptide or genomic marker as well as from a pathogen (virus or bacteria), from those enclosing at least one with a confidence level of 99%. This makes the NoOne platform the best performing ever in enabling a fast, highly reliable, cost-effective identification of the subset of biological samples belonging to the potentially diseased part of a population. This is of paramount importance for predictive screening of humans, plants or animals. NoOne will demonstrate its effectiveness in key relevant applications such as the binary detection of pancreatic cancer biomarkers, SARS-CoV-2 virus, the Xylella Fastidiosa bacterium and the assay of post translational peptides evidencing the phosphorylated forms regulating crosstalk with oncogenic signalling pathways.

Mots-clés : biosensors,organic bioelectronics,analytical chemistry,biological markers screening,organic filed effect transistors
Projet ERC : FUTUREFAUNA (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Université de Glasgow — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

Technology can enhance animal welfare by allowing animals greater control over their environment and choice over their social connections. Current animal-computer interfaces are often repurposed from human technology, neglecting animals' diverse physical capabilities, sensory perceptions, and cognitive processes. For instance, touch screens suited to human fingers pose challenges for animals with paws, beaks, or unique appendages, while human-based cognitive models underlying these interfaces potentially misinterpret or overlook critical aspects of animal cognition and behaviour. This disconnect between technology and animal users hinders effective interaction and constrains our capacity to gain accurate insights into animal minds. To address this challenge, FUTUREFAUNA's ultimate goal is to draw from empirical evidence to develop a comprehensive framework for designing, implementing and adapting technologies for animal users. The ambition is to fundamentally reshape how animals implement control over their environment and provide radically different opportunities for social connections to improve their well-being. This level of agency will allow us new ways to observe how animals make choices, solve problems, and navigate social situations when given tools that match their abilities. FUTUREFAUNA framework extends classic animal behaviour studies by offering new insights and scalable, documented approach.  In the long term, FUTUREFAUNA will open up a new frontier to expand the use of information technology. It tests the foundations of human-computer interaction by looking at new ways to understand users and creating entirely new avenues for studying animal intelligence and social structures. By providing animals with more nuanced and species-appropriate ways to interact with their environment and each other, researchers will be able to explore questions about animal consciousness, emotional intelligence, and cognitive flexibility that were previously out of reach.

Mots-clés : animal computer interaction,animal centered computing
Projet ERC : DaVinci-Switches (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Life Science
Panel : Molecules of Life: B iological  Mechanisms , Structures  and Functions
Entité participante : Université de Heidelberg — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1371987.86 €

Proteins are molecular machines that drive all major functions in cells. Controlling the activity of proteins in real time via light or chemicals is a central goal in synthetic biology. The design of switchable proteins, in particular single-chain, allosteric variants, however, is a challenging engineering problem thus-far mostly addressed by trial-and-error. DaVinci-Switches takes a radically new, data-driven perspective to fundamentally advance our understanding of protein allostery and accelerate and eventually rationalize the engineering of switchable proteins by interfacing synthetic biology with machine learning. We will establish a 'design by directed evolution' approach to create switchable proteins through receptor and effector fusion followed by phage-assisted in vivo directed evolution using synthetic gene circuits for selection. We will apply this novel pipeline to a diverse set of effector proteins and monitor the evolutionary process by next-generation sequencing (Objective 1). In parallel, we will perform an in-depth computational analysis of domain insertions within the natural protein repertoire. The combined, rich datasets will be used to train machine learning models to infer sequence patterns predictive of domain insertion tolerance and allosteric coupling between receptor-effector pairs (Objective 2). Finally, we will employ this unique model to design light- and drug-inducible variants of the Yamanaka cell reprogramming factors. These will provide the foundation of an Adeno-associated virus-based platform for cyclic, partial in vivo reprogramming of somatic cells with enormous potential for regenerative medicine, which will be evaluated in a murine model of drug-induced liver injury (Objective 3). DaVinci-Switches harnesses our key competences in protein engineering, synthetic biology and computation to reveal fundamental principles of allostery and enable transformative advances in the design of switchable proteins for research and medicine.

Mots-clés : phage assisted evolution,protein engineering,protein allostery,machine learning,partial transient reprogramming,regenerative medicine
Projet ERC : DynamITE (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems E ngineering
Entité participante : Université libre de Bruxelles — Pays : Belgique — Rôle : PI
Acronyme de l'entité : ULB
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1671339.0 €

The therapeutic effect of a drug is largely determined by how effectively it reaches its site of action. Drug distribution in the human body is defined by an intricate network of transporters, offering potential for dynamically controlling where a drug spends most of its time. DynamITE aims to provide the tools to manipulate this "highway network" of drug transport at will. DynamITE will exploit the common mechanism shared by transporters, that is the alternating-access. Every transporter must dynamically switch between different states to enable directional transport of its substrate through the biological membrane. At the molecular level, this involves important local and global changes in the protein's three-dimensional structure. The foundational methodology of DynamITE is a structural mass spectrometry approach that reports on such changes: hydrogen-deuterium exchange coupled to mass spectrometry (HDX-MS). I have demonstrated that HDX-MS can fingerprint the effects of drugs on the dynamic switching between states. DynamITE builds on this knowledge to identify and design modulators of transporter dynamics. A modulator that prevents the conformational changes underlying transport will block drug transport, while a modulator that increases the rate of conformational transitions will accelerate transport. DynamITE’s approach will be applied to selected drug transporters with proven critical roles in antibiotic resistance, drug toxicity, and drug transport into the brain. In parallel, DynamITE will advance the HDX-MS technique to make it applicable to living cells. Such a development will enable the observation of protein dynamics in cellulo, with a molecular level of resolution—something currently inaccessible. This methodological breakthrough be used to monitor drug transporters dynamics while in action within the cell. The toolbox developed within DynamITE will be applicable to any transporter for which targeted modulation of transport activity is desired.

Mots-clés : protein dynamics,transmembrane transport,drug transport,drug distribution,h d exchange mass spectrometry,nanobodies,solute carriers
Projet ERC : PENEA (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Soci al World and Its Interactions
Entité participante : Université libre de Bruxelles — Pays : Belgique — Rôle : PI
Acronyme de l'entité : ULB
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1495042.0 €

This project explores whether frustration with capitalist modernity leads East Asians to express discontent with economic development and to seek alternative futures. East Asian societies have experienced accelerated modernisation, but citizens in late-industrialised economies today reject hypercompetitive and unequal societies. In parallel, nostalgia has emerged as a major trend in consumer practices and cultural productions in the region. It is mostly contemplated as a cultural phenomenon. But when nostalgia expresses longing towards a pre-developmental past, it also belongs to the field of discontent with economic development and can shape citizens’ political economic mobilisation. The PENEA project therefore explores if East Asians long for their pre-developmental past, and if they mobilise for political economic change on this nostalgic basis? Combining sociology and political economy, it achieves three objectives: 1. documenting the expressions of nostalgia among East Asian citizens; 2. conceptualising these forms of nostalgia; 3. analysing if and how nostalgia is a source of mobilisation in East Asia. In East Asian societies that are post-developmental or developmental, expressions of longing for a recent economic past can be expected, and this longing can motivate actors to undertake individual or collective actions that produce political economic change. The PENEA project will test these hypotheses in high income, late-industrialisers (Japan, South Korea), middle-income Communist states (China, Vietnam) and fast-growing lower middle-income states (Philippines, Cambodia), through an innovative combination of traditional and social media analysis, surveys, interviews, participant observations and discourse analysis on textual and visual documents. The PENEA project is the first systematic, interdisciplinary and comparative study to identify political economic nostalgia in East Asian societies today, and to analyse how East Asians react to rapid development.

Mots-clés : nostalgia east asia development sociology political economy