Call for projects 1 - 2017 : Trans-disciplinary master’s degree projects
N° | Acronym | Project title | Applicant 1 / discipline | Applicant 2 / discipline | Applicant 3 / discipline | Key words |
1 | FMRP-SUMO-ABS |
Atomic and cellular impacts of the Fragile-X Mental Retardation Protein modifications by SUMO |
C Gwizdek / Biology | F Cazals / Digital sciences |
Fragile-X mental retardation protein, SUMO, dynamics of multiprotein complexes , structural modélisation |
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2 | MecanoAdipo |
Modeling the mechanical feedback of adipogenesis |
E Honoré / Biology | B Mauroy / Maths | JF Tanti / Biology |
Adipose tissue, adipogenesis, mechanical force, mechanotransduction, mathematical modeling |
4 | IDEX_MITO |
Détection, classification and characterization of mitochondrial networks : application to Alzheimer disease and Cancer |
X Descombes/ digital sciences | M Chami / Biology | F Bost / Biology | |
6 | I2MD |
Identification of inhibitors disrupting MITF interactions with DNA |
A Burger / Chemistry | C Bertolotto / Biology | Biology, Chemistry, MITF, inhibition, fluorescence, polyamides | |
7 | REDAC | Search and characterization of anti-cancer invasion drugs | M Franco / Biology | M Mehiri / Chemistry |
Anticancer drugs, Small G protein, invasion, Biochemistry, chemical synthesis, molecule screening |
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8 | DEMOTECH |
Development of molecules for therapy against chemoresistant blood diseases |
A Martin / Chemistry | G Robert / Biology | T Cluzeau / Medical sciences |
Blood diseases, Myelodysplastic syndromes, resistance, inhibitors, anticancer drugs |
9 | COMICS |
Identification of new generation immunostimulatory and antimicrobial components |
T Michel / Chemistry | L Boyer / Biology |
Parasite, Leishmaniose, natural components, immunostimulation |
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10 | mTrans | Role of distance and energy in vectorial lipid transport | G Drin / Biology | A Seminara / Physics |
Transfert proteins, lipid gradient, in vitro assays, distance, microfluidics |
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11 | MpH | Fast measurements of intracellular pH using microfuidic systems | L Counillon / Biology | X Noblin / Physics | ||
12 | NMLA-scRNASEQ | New machine learning approaches for single cell RNA seq analysis | A Paquet / Biology | M Barlaud / Digital sciences |
Single cell, RNASeq, big data, machine learning, gene network, biostatistics, deconvolution, airway epithelium diseases |
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