TY - JOUR
T1 - Data-driven bioinformatics to disentangle cells within a tissue microenvironment
AU - Tegner, Jesper
AU - Gomez-Cabrero, David
N1 - KAUST Repository Item: Exported on 2022-04-18
Acknowledgements: J.N.T and D.G-C acknowledge support from King Abdullah University of Science and Technology.
PY - 2022/4/13
Y1 - 2022/4/13
N2 - Molecular profiling of clinical tissue samples is at the core of precision medicine. Yet, to elucidate the contribution of mixed cell types and detect changes in cell populations in response to infections or drugs is challenging. Recent advances using machine learning promise to learn explanatory models directly from data.
AB - Molecular profiling of clinical tissue samples is at the core of precision medicine. Yet, to elucidate the contribution of mixed cell types and detect changes in cell populations in response to infections or drugs is challenging. Recent advances using machine learning promise to learn explanatory models directly from data.
UR - http://hdl.handle.net/10754/676275
UR - https://linkinghub.elsevier.com/retrieve/pii/S0962892422000812
U2 - 10.1016/j.tcb.2022.03.009
DO - 10.1016/j.tcb.2022.03.009
M3 - Article
C2 - 35430125
SN - 0962-8924
JO - Trends in Cell Biology
JF - Trends in Cell Biology
ER -