Call for projects 1 - 2017 : Trans-disciplinary master’s degree projects

Call for projects 1 - 2017 : Trans-disciplinary master’s degree projects

12 projects were evaluated by the scientific council and 10 projects were accepted.
Acronym Project title Applicant 1 / discipline Applicant 2 / discipline Applicant 3 / discipline Key words


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

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



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



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



Identification of new generation

immunostimulatory and antimicrobial components

T Michel / Chemistry L Boyer / Biology  

Parasite, Leishmaniose, natural components,


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,


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