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RADIation-induced neurOtoxicity assessed by spatio-temporal modelling combined with Artificial Intelligence after brain raDiothErapy – RADIO-AIDE
RADIO-AIDE is a multidisciplinary project that aims to develop advanced spatio-temporal models and new Artifical Intelligence tools for brain Magnetic Resonance Imaging (MRI) data processing to : a) generate new knowledge about the underlying neurotoxic mechanisms implied in the initiation and tempo
Functioning from the assimilation of structural traits. Understanding wheat functioning from the assimilation of high-throughput observations into plant simulation models – FFAST
FFAST aims at describing wheat genotypes functioning through an innovative model-assisted phenotyping strategy. Currently, studies on field phenotyping are mostly focused on exploiting directly structural traits observations (e.g. leaf area, height) to establish statistical models with genetic chara
Statistical develoPments and ApplicatioN on Oxygenic photogRAnules for longitudinal Multi-omICS data – PANORAMICS
Oxygenic photogranules (OPGs) could turn wastewater treatment in circular bioeconomy by capturing much of the energetic and chemical value of wastewater in their biomass. But essential knowledge on their formation and life cycle is still missing and needed for conducting a bioprocess based on OPGs.
Thrombogenicity Reduction by Means of Surface Structures – A combined In-silico and In-vitro study – ThromboSurf
Several treatments of cardiovascular diseases involve artificial heart valves, ventricular assist devices, grafts, or stents, which are all blood-contacting medical devices. The haemocompatibility of medical devices remains the major challenge in their development. An insufficient haemocompatibility
Integrated Sequencing and Structural Analysis of RNA Probing Experiments – INSSANE
The structure of RNA molecules and their complexes are crucial for understanding biology. Notorious examples of large RNAs include the genomes of RNA viruses (Influenza, HIV, Chikungunya, SARS-CoV2...), whose lengths exceed the current capabilities of predictive computational methods, as well as hig
Model-based enzyme evolution – MoBEE
Directed evolution is nowadays the most efficient approach to design enzymes with improved or new properties. This experimental method subjects a candidate sequence to cycles of diversification and selection that mimic the natural evolutionary process. In practice, however, it requires to start with
Simulation of PErCutaneoUs Liver tumor Ablation in virtual Reality – SPECULAR
Radiofrequency ablation of liver tumors has become the preferred procedure for many pa-tients. However, despite their many advantages, these percutaneous procedures require ad-vanced skills from the practitioner, especially for procedures involving soft and mobile organs such as the liver. The objec
Model Of coLon epIthElial aRchitecturE – MOLIERE
Intestinal epithelium is a single layer of cells exposed to external aggressive conditions, that is renewed every 4–5 days, that makes it one of the most sensitive part of human body. Its tissue homeostasis is highly sensitive to proliferation and cell migration; events occurring in a specific micro
Dynamics of DNA repair proteins at nucleosomes – DYPROSOME
We propose a combined computational and experimental study of the molecular mechanisms by which repair proteins identify the earliest stages of DNA damage in chromatin. DNA damage repair processes (DDR) are tightly regulated among several pathways operating for different types of damage. However, th
End-to-End Deep learning for Precision Medicine through Metagenomics and cost-sensitive data integration – DeepIntegrOmics
In chronic diseases such as cardiometabolic diseases (CMD), the use of intestinal microbiota as a source of patient stratification and of innovative treatment is on the rise. As a “super integrator" of the patient's condition metagenomics is poised to play a key role in precision medicine. However,
Controlling unruptured intracranial aneurysms using Fluid-Structure interaction and Deep Reinforcement Learning – siCURE
Recent advances in the development of Deep Reinforcement Learning (DRL) algorithms have led to the advent of deep neural networks, powerful tools capable of leveraging the ever-increasing volume of numerical and experimental data generated for research and engineering purposes into novel insight and
Consistency-Based Patient-Motion Correction in Pinhole and Conventional SPECT – SPECT-Motion-eDCC
Single Photon Emission Computed Tomography (SPECT) refers to a technique for 3D imaging of a radioactive tracer that has been administered to a patient, in order to track certain biological functions. SPECT remains principally a diagnostic tool, but is now gaining increased usage for radionuclide-ba
Understanding Keloid Disorders: A multi-scale in vitro/in vivo/in silico approach towards digital twins of skin organoids on the chip – S-Keloid
Mathematical and numerical modelling approaches allow us to integrate pathological processes that occur across different scales: cell, cells assembly, and tissue. The S-Keloid project aims to investigate the role of mechanical and inflammatory environmental factors on cells associated with keloid di
Advancing genotype to phenotype Studies by considering TE Variability and Epivariabilty – STEVE
Genetic variation underpins inherited differences in traits, yet genome-wide association studies (GWAS) only explain part of this inheritance. One key explanation is that so far GWAS have largely neglected transposable element (TE) sequences, despite their prevalence and their often major effects on
Organoid Phenotypes Mapping and Modeling : Toward an Endocrine Disruptors Classification – MORPHEUS
Organoid are a recent technology very promising in different medical applications(Characterization of molecules effect, drug choice for personalized medicine). Computational tools are now required for fully taking benefit from this approach. With this respect, this project aims at filling this gap i
Reproducibility with VIP – ReproVIP
In the last few years, there has been a growing awareness of reproducibility concerns in many areas of science. In a recent study, the analysis of a single neuroimaging dataset by 70 independent analysis teams reveals substantial variability in reported results, with high levels of disagreement acro
Leveraging pleiotropy in human genetic architecture by building a map of pleiotropy using machine learning – PleioMap
Although pleiotropy, which occurs when a genetic element has a causal effect on at least two traits, is thought to play a central role in the genetic architecture of complex traits and diseases, it is a poorly understood mechanism. Here, we reexamined known concepts of human genetics through the pri
Small vessel diseases: Ultra-realistic Microstructure computational Model to refine Individual Treatment – SUMMIT
Small vessel disease (SVD) accounts for 25% of strokes and is the second most common cause of dementia after Alzheimer's disease. Unlike other causes of stroke, SVD manifests itself years before the stroke by the accumulation of tissue damage. Although heterogeneous, these lesions appear on MRI as w
Artificial Metabolic Networks – AMN
While the primary role of metabolism is chemical conversions, can it also serve as an information processing device? To answer this question, we propose to encode various microbial metabolic models into Artificial Metabolic Networks (AMNs), which can be trained on experimental data or model simulati
Deciphering protein carbohydrate interactions using machine learning approaches: application to the key protein of placental malaria disease – SugarPred
Protein-carbohydrate (PC) interactions play a key role in various biological processes. In particular, PC interactions govern infected erythrocyte (IE) adhesion on placental cells during placental malaria (PM) leading to severe pathological conditions. Experimental description of PC interfaces remai
Understanding the self-assembly of the nervous system of Hydra vulgaris – REBIRTH
Self-assembly of biological organisms is fascinating as, somehow, bodies put themselves together without external directions, to yield robust, resilient and adaptive living systems. This is particular dramatic in the cnidarian Hydra vulgaris, a small and transparent polyp with unique regenerative pr
Modeling Intestinal Glucose Absorption for Diabetes Prediction – MIGAD
Type 2 Diabetes (T2D) is the main epidemic of this century. A recent hypothesis of medical research is that an important cause of T2D may be the abnormal regulation of glucose absorption in the small intestine. The objective of the present project is to investigate the relative contribution of ea
Developmental mechanics of brain evolution – DMOBE
The geometry of the cerebral cortex is related to its cellular, connective and functional organisation. This relationship is established during development, as the cortex folds following stereotypic patterns. Folding patterns are thought to reflect patterned gene expression. But how to distinguish g
Multi-scale modelling of transport in the gastrointestinal tract – TransportGut
The gastrointestinal tract involves many biological, chemical and physical phenomena to secure the absorption of nutrients from our food. Also, specific sites of the digestive mucosa are gateways to our immunologic system which pave the way for the development of innovative oral therapeutic strategi
controlliNg a magnEtic Micro-swimmer in cOnfined and complex environments – NEMO
NEMO aims to develop numerical methods to control a micro-robot swimmer in the arteries of the human body. These robots could deliver drugs specifically to cancer cells before they form new tumors, thus avoiding metastasis and the traditional chemotherapy side effects. NEMO will focus on micro
Interactive Pharmacophore using Augmented Reality – PIRATE
Many drugs act through interaction with biomolecules, called targets. Finding new drugs can benefit from Virtual Screening which allows one to consider millions of molecules, in particular with the use of a 3D-pharmacophore, a 3D representation of molecular properties. 3D-pharmacophores are built au
Adequate graph structures for third-generation sequencing data exploration – Agate
In the last years, third-generation sequencing (TGS) changed the whole genomic landscape. Providing long-range information that can overcome most genomic repetitions, we can now obtain chromosome-scale assembled sequences even from vertebrate genomes. However, flawless de novo assembly is still a ch
LivChrom: The Living Chromatin framework to investigate the functional compartmentalization of the genome – LivChrom
Eukaryotic DNA is wrapped around histone octamers forming the so-called chromatin fiber. Information on the genome activity is partly encoded by the local Chromatin State, characterized by various bichemical properties such as histone modifications. In nucleus, early observations revealed a non-rand
Personalized virtual transcatheter aortic valve assessment – AorticVirtu_et_al
Valve thrombosis is a recent discovery for which it can be suspected that changes in local hemodynamics associated with implantation of the valve after TAVR stand as a contributing factor. No independent studies are currently published on changes in aortic hemodynamics after TAVR depending on the pa
Holistic explainable artificial intelligence schemes for lung cancer prognosis – Hagnodice
Artificial Intelligence and its current success in a variety of fields influences also considerably the field of health care. A great number of algorithms currently provide powerful solutions, assisting medical doctors in their everyday practice in particular for diagnostic purposes. The ambition o
Analysis Modelling Simulation Multiscale – NEMATIC
The objective of the project is to experimentally characterize, analyse, model and simulate the multi-scale dynamics of complex and growing branching random networks. Both analytical and numerical means as well as experimental realizations are used and developed. In a biological context, the growth
Model-driven Analysis of Gene Expression Economy – MAGEEc
Despite the large amount of available data, the precise biophysical principles governing the interdependence between cell growth, gene expression and the allocation of cellular resources remain still unexplained. This proposal aims at understanding the regulation of the complex cellular economy
Deep lEarning tooLs for selectIve iNtErnal rAdiation ThErapy of hepatic tumours – DELINEATE
Liver cancer is the sixth most common cancer in the world but the second leading cause of cancer mortality in men. Among the different types of liver cancer, some can be treated by selective internal radiation therapy (SIRT), which consists in injecting into the selected hepatic arteries yttrium-90
Comprehensive modeling of myocardial shear wave elastography for non-invasive assessment of cardiac function – ElastoHeart
Cardiac pathologies are often characterized by a change of myocardial stiffness. For example, some types of heart failure display changes in ventricular stiffness. Stiffness is an intrinsic property of soft tissues that reflects the pathological states. However current clinical imaging tools such as
Inferring stem cell quiescence dynamics from time-stamped single-molecule measurements – QDynamics
Adult stem cells (SCs) often “rest” in quiescence, itself a dynamic state composed of sub-states that SCs transit through. Using the neural stem cell (NSC) niche of the zebrafish adult brain, we will combine scRNAseq, single-molecule gene expression analyses and direct temporal measurement in indivi
Fish In Silico with Hydrodynamic and Social Interactions Forces – FISHSIF
Collective movement in living organisms is a phenomenon of self-organization of a large number of individuals observed in nature from the micrometer scale (bacteria, plankton) to meters (birds) or even kilometers (school of sardines). This organization at a scale much larger than each individual is
QUantitative Antimicrobial resistance: control Strategies and evolutionary Adaptation of parasitical virulence and Resistance – QUASAR
In view of the multiple pathogen evolution capabilities, the long-term efficacy of antimicrobials is a major public health problem. Defining sustainable strategies for managing antimicrobials efficiency, in space and time, must: (i) consider the continuous character of antimicrobial resistance -i.e.
Computational Approaches for Multimodal Data Integration in Biomedicine – CAMUDI
High-throughput technologies are generating a wealth of biological data. These data yield unprecedented opportunities to better understand biological systems in healthy and pathological states but also bring heavy computational challenges. A fundamental challenge is the integration of data from mult