Identification of metabolic biomarkers in idiopathic pulmonary arterial hypertension using targeted metabolomics and bioinformatics analysis

Pulmonary arterial hypertension (PAH) is a life-threatening disease with a poor prognosis, and metabolic abnormalities play a critical role in its development. This study used metabolomics, machine learning algorithms and bioinformatics to screen for potential metabolic biomarkers associated with th...

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Veröffentlicht in:	Scientific reports Jg. 14; H. 1; S. 25283 - 15
Hauptverfasser:	Yang, Chuang, Liu, Yi-Hang, Zheng, Hai-Kuo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 25.10.2024 Nature Publishing Group Nature Portfolio
Schlagworte:	631/114 692/308 692/4019 692/53 692/699 Adult Algorithms Biochemical pathways Bioinformatics Biomarkers Biomarkers - blood Biosynthesis Case-Control Studies Computational Biology - methods Diagnosis Familial Primary Pulmonary Hypertension - blood Familial Primary Pulmonary Hypertension - genetics Familial Primary Pulmonary Hypertension - metabolism Female High-performance liquid chromatography Humanities and Social Sciences Humans Hypertension Idiopathic pulmonary arterial hypertension Learning algorithms Liquid chromatography Machine Learning Male Mass spectrometry Mass spectroscopy Metabolism Metabolites Metabolome Metabolomics Metabolomics - methods Middle Aged multidisciplinary Phenotypes Pulmonary hypertension Science Science (multidisciplinary) Spermine Tryptophan Biomarkers Idiopathic pulmonary arterial hypertension Metabolomics Biochemical pathways Machine learning
ISSN:	2045-2322, 2045-2322
Online-Zugang:	Volltext
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