Bioinformatics strategy to identify the pathogenesis of intracerebral hemorrhage

Objective: A bioinformatics approach was used to determine the key targets for the pathogenesis of intracerebral hemorrhage (ICH). Methods: Entering "intracerebral hemorrhage " as keywords, we searched for and downloaded ICH-related targets using the GeneCards database. Meanwhile, we collected the relevant targets from cortex through GeneCards database. Then, downloaded data were integrated so as to obtain the intersected genes from the targets between ICH and cortex, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were conducted using R language. Lastly, we map the key genes from protein-protein interaction (PPI) into GO and KEGG so as to acquire hub genes in cortex subjected to ICH injury. Results: After inputting the terms "intracerebral hemorrhage" into GeneCards, 1159 targets were recognized in the GeneCards database, 87465 cortex-related targets were retrieved. Furthermore, 1125 intersected genes were identified through Venny analysis. Subsequently, GO enrichment analysis revealed that these genes are primarily involved in biological processes such as wound healing, regulation of body fluid levels, response to peptides, positive regulation of responses to external stimuli, and cytokine-mediated signaling pathways. KEGG pathway enrichment analysis indicated that these genes are mainly associated with inflammatory pathways, including PI3K-AKT, JAK-STAT, and HIF-1. Conclusions: Our results comprehensively illustrated the potential targets involved in the pathogenesis of ICH, therefore, providing new insights for molecular therapy of ICH in future clinic trial development.

Authors

Publication Details

Journal
New discovery.
Published
2024-08-10
DOI
https://doi.org/10.61958/ndxr6013
Primary Topic
Intracerebral and Subarachnoid Hemorrhage Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Bioinformatics strategy to identify the pathogenesis of intracerebral hemorrhage

Jie Sun, Zhenhao Liu, Tingting Liu, Haiyan Yin et al.
New discovery.
Intracerebral and Subarachnoid Hemorrhage Research
article

Bioinformatics strategy to identify the pathogenesis of intracerebral hemorrhage

Jie Sun, Zhenhao Liu, Tingting Liu, Haiyan Yin, Ze-Kang Liu, Hai‐Yang Suo, Zhi-Kun Lu
article en

Abstract

Objective: A bioinformatics approach was used to determine the key targets for the pathogenesis of intracerebral hemorrhage (ICH). Methods: Entering "intracerebral hemorrhage " as keywords, we searched for and downloaded ICH-related targets using the GeneCards database. Meanwhile, we collected the relevant targets from cortex through GeneCards database. Then, downloaded data were integrated so as to obtain the intersected genes from the targets between ICH and cortex, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were conducted using R language. Lastly, we map the key genes from protein-protein interaction (PPI) into GO and KEGG so as to acquire hub genes in cortex subjected to ICH injury. Results: After inputting the terms "intracerebral hemorrhage" into GeneCards, 1159 targets were recognized in the GeneCards database, 87465 cortex-related targets were retrieved. Furthermore, 1125 intersected genes were identified through Venny analysis. Subsequently, GO enrichment analysis revealed that these genes are primarily involved in biological processes such as wound healing, regulation of body fluid levels, response to peptides, positive regulation of responses to external stimuli, and cytokine-mediated signaling pathways. KEGG pathway enrichment analysis indicated that these genes are mainly associated with inflammatory pathways, including PI3K-AKT, JAK-STAT, and HIF-1. Conclusions: Our results comprehensively illustrated the potential targets involved in the pathogenesis of ICH, therefore, providing new insights for molecular therapy of ICH in future clinic trial development.

New discovery.
Openalex Percentile: Top 79%
Intracerebral and Subarachnoid Hemorrhage Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Bioinformatics strategy to identify the pathogenesis of intracerebral hemorrhage — Jie Sun, Zhenhao Liu, et al. · New discovery. (2024) | TGRS Research Map | TGRS