Using Data-Driven Algorithms with Large-Scale Plasma Proteomic Data to Discover Novel Biomarkers for Diagnosing Depression

Given recent technological advances in proteomics, it is now possible to quantify plasma proteomes in large cohorts of patients to screen for biomarkers and to guide the early diagnosis and treatment of depression. Here we used CatBoost machine learning to model and discover biomarkers of depression...

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Vydané v:	Journal of proteome research Ročník 23; číslo 9; s. 4043
Hlavní autori:	Ma, Simeng, Li, Ruiling, Gong, Qian, Lv, Honggang, Deng, Zipeng, Wang, Beibei, Yao, Lihua, Kang, Lijun, Xiang, Dan, Yang, Jun, Liu, Zhongchun
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States 06.09.2024
Predmet:	Algorithms Area Under Curve Biomarkers - blood Blood Proteins - analysis Blood Proteins - metabolism Depression - blood Depression - diagnosis Female Humans Machine Learning Male Proteome - analysis Proteome - metabolism Proteomics - methods ROC Curve Biomarkers Depression CatBoost Proteomic
ISSN:	1535-3907, 1535-3907
On-line prístup:	Zistit podrobnosti o prístupe
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