About: Novel biomarkers for pre-eclampsia detected using metabolomics and machine learning

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scholarly article by Louise C. Kenny et al published July 2005 in Metabolomics

Attributes	Values
rdf:type	Item
description	wetenschappelijk artikel (nl) наукова стаття, опублікована в липні 2005 (uk) im Juli 2005 veröffentlichter wissenschaftlicher Artikel (de) scholarly article by Louise C. Kenny et al published July 2005 in Metabolomics (en)
publication date	wds:Q56974546-0C166CAC-58EF-4156-A1D7-5BE471E02EB0
publication date	2005-07-01 00:00:00Z (xsd:dateTime)
exact match	wds:Q56974546-18E61F18-1D7A-4DB3-925E-BC7201628B07
exact match	https://scigraph.springernature.com/pub.10.1007/s11306-005-0003-1
cites work	wds:Q56974546-C6533BC1-5385-474C-BB15-E6B523510D2E wds:Q56974546-F5669B39-C331-4423-B9D5-4A201F3F0BA9
cites work	Preeclampsia: an endothelial cell disorder Preeclampsia is associated with a serum factor cytotoxic to human endothelial cells.
author name string	wds:Q56974546-486ED321-9810-43C0-821C-C3D723BAF761 wds:Q56974546-4F4A5304-1D66-4F57-B2CC-507442B456E2
author name string	Douglas B. Kell Philip N. Baker
rdfs:label	Novel biomarkers for pre-eclampsia detected using metabolomics and machine learning (en) Novel biomarkers for pre-eclampsia detected using metabolomics and machine learning (nl)
skos:prefLabel	Novel biomarkers for pre-eclampsia detected using metabolomics and machine learning (en) Novel biomarkers for pre-eclampsia detected using metabolomics and machine learning (nl)
name	Novel biomarkers for pre-eclampsia detected using metabolomics and machine learning (en) Novel biomarkers for pre-eclampsia detected using metabolomics and machine learning (nl)
author	wds:Q56974546-16985749-E162-4A5F-B15D-40ECC1328466 wds:Q56974546-86700AA4-121F-4223-AB34-A66243DF9AD0 wds:Q56974546-CBEFFB18-F324-43A9-8A89-44AF8C1FEFC3 wds:Q56974546-D84461AC-4388-42DA-947E-2110DD662A6F
author	Louise Kenny Warwick Dunn David I. Ellis Jenny Myers
title	wds:Q56974546-7940647B-FAB6-4E1D-9BB2-72D85EA45760
title	Novel biomarkers for pre-eclampsia detected using metabolomics and machine learning (en)
page(s)	wds:Q56974546-9CEDC4B4-308A-464B-BAD7-FBE368FA3929
page(s)	227-234
instance of	wds:Q56974546-08C10F8E-8B5C-4D77-B4C6-D9A5A9C40333
instance of	scholarly article
main subject	wds:Q56974546-63A93FE2-9AC0-4074-BFD9-275D28E48B0D wds:Q56974546-6DD8AD5D-9EFC-4282-8D8A-461ED2694F04 wds:Q56974546-7DB512BD-CC70-4AAA-A92C-1B33742BB973 wds:Q56974546-A0A16CD9-151D-46D5-89AE-0323C0E14E28
main subject	machine learning pre-eclampsia metabolomics biomarker
published in	wds:Q56974546-04392ED1-C92E-45AE-AF0A-4D126A715668
published in	Metabolomics
issue	wds:Q56974546-96A70CFF-B67C-450A-A770-B48623F85658
volume	wds:Q56974546-F0427E83-A395-4AE3-B6AE-DCA6CA16A67E
issue	3
volume	1
DOI	wds:Q56974546-D0BE5E0D-491F-4424-87D4-EEE7AA5E5B14
DOI	http://dx.doi.org/10.1007/S11306-005-0003-1
DOI	10.1007/S11306-005-0003-1
is about of	https://www.wikidata.org/wiki/Special:EntityData/Q56974546
is cites work of	Metabonomic characterization of early atherosclerosis in hamsters with induced cholesterol Metabolic fingerprinting as a diagnostic tool. Meet the human metabolome. Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy The need for external validation in machine olfaction: emphasis on health-related applications. UPLC-MS metabolic profiling of second trimester amniotic fluid and maternal urine and comparison with NMR spectral profiling for the identification of pregnancy disorder biomarkers Metabolomic mapping of atypical antipsychotic effects in schizophrenia. Detection and identification of novel metabolomic biomarkers in preeclampsia Metabolomic biomarkers: search, discovery and validation First-trimester prediction of preeclampsia using metabolomic biomarkers: a discovery phase study Markers of preeclampsia and the relationship to cardiovascular disease: review of the twenty-first century literature A Dormant Microbial Component in the Development of Preeclampsia Integration of metabolomic and transcriptomic networks in pregnant women reveals biological pathways and predictive signatures associated with preeclampsia Predicting metabolic biomarkers of human inborn errors of metabolism The metabolome 18 years on: a concept comes of age Machine learning to detect signatures of disease in liquid biopsies - a user's guide. Navigating the human metabolome for biomarker identification and design of pharmaceutical molecules. Aromatic amino acid biomarkers of preeclampsia--a nuclear magnetic resonance investigation Metabolomic Strategies Involving Mass Spectrometry Combined with Liquid and Gas Chromatography
is cites work of	wds:Q37748773-E31F9070-B9D1-49D4-AB51-457C7792C81F wds:Q55043427-5756931E-8D1F-4A9D-8F5B-658E1020195B wds:Q44712547-FBEE282A-1A49-49B1-AD60-08EB003A2750 wds:Q28080314-45FA6C0B-C87A-4E79-9CB6-1DAA5AB7BED4 wds:Q37196179-50328499-EBAD-4D95-8933-57051959BABD wds:Q38735199-FB2D8D7D-731A-413B-9DF9-ED955C02CCDC wds:Q38993393-238B963D-E2D6-42A7-A211-F0D2B7B8EB69 wds:Q46433983-C077B59B-B4A9-446E-A7D9-F85D1921815E wds:Q45943388-3DADBEAF-5A69-4491-BA17-641C86477BE0 wds:Q58040335-1B412B45-1FA3-4A81-BA7B-8101B21408D3 wds:Q34170091-41C9D3C2-5EF0-4123-A735-E23159C8F35B wds:Q34699756-9877D1EC-4BB5-4690-AC07-8FC43E0D032F wds:Q46585274-4BB47651-5231-4B4F-A44F-9E5D0825888F wds:Q37018001-7F354822-983C-4915-800A-31C5B612A22F wds:Q28069689-972AF53E-2D9C-4F67-9B5E-C593F19D173F wds:Q38210963-C56B6A5F-F0BD-4039-8985-39FF69C74A40 wds:Q56974486-818BFFC0-C6C8-4FEA-AD34-4CC28A522C81 wds:Q34620002-3A8755C5-C50C-46DA-AC67-1B4757D0D64E wds:Q37780690-DF11452A-7188-4D65-AB22-E1FBC11D905C

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