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...

Full description

Saved in:

Bibliographic Details
Published in:	Journal of proteome research Vol. 23; no. 9; p. 4043
Main Authors:	Ma, Simeng, Li, Ruiling, Gong, Qian, Lv, Honggang, Deng, Zipeng, Wang, Beibei, Yao, Lihua, Kang, Lijun, Xiang, Dan, Yang, Jun, Liu, Zhongchun
Format:	Journal Article
Language:	English
Published:	United States 06.09.2024
Subjects:	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
Online Access:	Get more information
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!