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Identification of Key Proteins and Pathways in Myocardial Infarction Using Machine Learning Approaches

ABSTRACT: Acute myocardial infarction (AMI) is a leading cause of global morbidity and mortality, requiring deeper insights into its molecular mechanisms for improved diagnosis and treatment. This study combines proteomics, multi-omics, and machine learning (ML) to identify key proteins and pathways associated with AMI.

ORGANISM(S): Homo Sapiens

SUBMITTER: Xiaomei Li

PROVIDER: PXD062794 | iProX | Thu Apr 10 00:00:00 BST 2025

REPOSITORIES: iProX

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Identification of key proteins and pathways in myocardial infarction using machine learning approaches.

Liu Chang C Zhang Xing X Xie Qian Q Fang Binbin B Liu Fen F Luo Junyi J Aihemaiti Gulandanmu G Ji Wei W Yang Yining Y Li Xiaomei X

Scientific reports 20250604 1

Acute myocardial infarction (AMI) is a leading cause of global morbidity and mortality, requiring deeper insights into its molecular mechanisms for improved diagnosis and treatment. This study combines proteomics, transcriptomics and machine learning (ML) to identify key proteins and pathways associated with AMI. Plasma samples from 48 AMI patients and 50 healthy controls (HC) were used for proteomic sequencing. Differentially expressed proteins (DEPs) were identified and analyzed for pathway en ...[more]

PMID: 40467768

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