Identification of Key Genes Based on Integrated Differentially Expressed Genes Analysis in RNA-seq of Breast Cancer

Differential analysis methods are used to identify significant changes in gene expression levels under different conditions. In this paper, a framework for DEGs analysis based on a combined centrality method with topological potential is proposed. Differentially Expressed Genes (DEGs) usually identified through differential analysis methods. The integrated analysis has been recommended in two stages. At first, DEGs are recognized. NOIseq is choosen to solve the problem of DEGs recognition. Secondly, DEGs are used to identify key genes. PPI network is constructed through the DEGs. In the PPI network, a novel combined centrality method with topological potential is used to identify the key genes. Finally, based on genomics data of breast cancer, the key genes are successfully identified.

Authors

Institutions

Publication Details

Published
2025-07-18
DOI
https://doi.org/10.1109/eeais66172.2025.11171044
Primary Topic
Gene expression and cancer classification
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Identification of Key Genes Based on Integrated Differentially Expressed Genes Analysis in RNA-seq of Breast Cancer

Xiao Wen-juan, Minghua Liu, Ling Guo, Shuo Zhai
Gene expression and cancer classification
article

Identification of Key Genes Based on Integrated Differentially Expressed Genes Analysis in RNA-seq of Breast Cancer

Xiao Wen-juan, Minghua Liu, Ling Guo, Shuo Zhai
article en

Abstract

Differential analysis methods are used to identify significant changes in gene expression levels under different conditions. In this paper, a framework for DEGs analysis based on a combined centrality method with topological potential is proposed. Differentially Expressed Genes (DEGs) usually identified through differential analysis methods. The integrated analysis has been recommended in two stages. At first, DEGs are recognized. NOIseq is choosen to solve the problem of DEGs recognition. Secondly, DEGs are used to identify key genes. PPI network is constructed through the DEGs. In the PPI network, a novel combined centrality method with topological potential is used to identify the key genes. Finally, based on genomics data of breast cancer, the key genes are successfully identified.

Minzu University of China (CN)
Openalex Percentile: Top 77%
Gene expression and cancer classification
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.