Please log in to take part in the discussion (add own reviews or comments).
Cite this publication
More citation styles
- please select -
%0 Journal Article
%1 maric2022early
%A Marić, Ivana
%A Contrepois, Kévin
%A Moufarrej, Mira N
%A Stelzer, Ina A
%A Feyaerts, Dorien
%A Han, Xiaoyuan
%A Tang, Andy
%A Stanley, Natalie
%A Wong, Ronald J
%A Traber, Gavin M
%A others,
%D 2022
%I Elsevier
%J Patterns
%K longitudinal modeling multi multiomics myown omics prediction preeclampsia pregnancy
%N 12
%P 100655
%T Early prediction and longitudinal modeling of preeclampsia from multiomics
%V 3
@article{maric2022early,
added-at = {2023-01-14T21:22:42.000+0100},
author = {Mari{\'c}, Ivana and Contrepois, K{\'e}vin and Moufarrej, Mira N and Stelzer, Ina A and Feyaerts, Dorien and Han, Xiaoyuan and Tang, Andy and Stanley, Natalie and Wong, Ronald J and Traber, Gavin M and others},
biburl = {https://www.bibsonomy.org/bibtex/27da61556d4feba77c47b08ce19be7737/becker},
description = {impactfactor = {4.39},impactfactor-year = {2022},impactfactor-source = {https://www.resurchify.com/impact/details/21101028388}},
interhash = {47a0b8d17c886a9030b2d609dc08f2a2},
intrahash = {7da61556d4feba77c47b08ce19be7737},
journal = {Patterns},
keywords = {longitudinal modeling multi multiomics myown omics prediction preeclampsia pregnancy},
number = 12,
pages = 100655,
publisher = {Elsevier},
timestamp = {2023-10-05T04:55:48.000+0200},
title = {Early prediction and longitudinal modeling of preeclampsia from multiomics},
volume = 3,
year = 2022
}