Journal article

Single-cell RNA-seq and computational analysis using temporal mixture modeling resolves T(H)1/T-FH fate bifurcation in malaria

Tapio Lonnberg, Valentine Svensson, Kylie R James, Daniel Fernandez-Ruiz, Ismail Sebina, Ruddy Montandon, Megan SF Soon, Lily G Fogg, Arya Sheela Nair, Urijah N Liligeto, Michael JT Stubbington, Lam-Ha Ly, Frederik Otzen Bagger, Max Zwiessele, Neil D Lawrence, Fernando Souza-Fonseca-Guimaraes, Patrick T Bunn, Christian R Engwerda, William R Heath, Oliver Billker Show all

Science Immunology | AMER ASSOC ADVANCEMENT SCIENCE | Published : 2017

Grants

Awarded by Wellcome Trust


Awarded by European Research Council grant ThSWITCH


Awarded by Australian National Health and Medical Research Council Project grant


Awarded by University of Queensland


Awarded by Marie Curie Initial Training Networks grant "Machine Learning for Personalized Medicine"(EU FP7-PEOPLE)


Funding Acknowledgements

This work was supported by Wellcome Trust (no. WT098051), European Research Council grant ThSWITCH (no. 260507), Australian National Health and Medical Research Council Project grant (number 1028641), and Career Development Fellowship (no. 1028643), University of Queensland; Australian Infectious Diseases Research Centre grants; and the Lister Institute for Preventive Medicine. K.R.J. was supported by grants from European Molecular Biology Laboratory Australia and OzEMalaR. F.O.B. was supported by the Lundbeck Foundation. M.Z. was supported by the Marie Curie Initial Training Networks grant "Machine Learning for Personalized Medicine" (EU FP7-PEOPLE Project Ref 316861, MLPM2012).