Identification of key genes of different phenotypes.

Identification of key genes of different phenotypes.

<p>(A) Dynamic tree cut to get modules related to cluster C1 and cluster C2. (B) The correlation between modules and clusters. Different colors indicate different correlation coefficients. The value in parentheses represents P-value. (C) Dynamic tree cut to get modules related to control and D...

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Bibliographic Details
Main Author: Hongmin Luo (2142307) (author)
Other Authors: Yuxuan Cao (12490494) (author), Liping Guo (596697) (author), Hui Li (32376) (author), Yingying Yuan (9674249) (author), Fan Lu (490738) (author)
Published: 2025
Subjects:
Microbiology
Cell Biology
Genetics
Molecular Biology
Evolutionary Biology
Immunology
Developmental Biology
Marine Biology
Cancer
Infectious Diseases
Biological Sciences not elsewhere classified
ward &# 8217
responsive protein 12
potential biological markers
logistic regression analysis
gene expression omnibus
via different algorithms
related factor 2
differentially expressed genes
distinguish different phenotypes
determine different phenotypes
immune cell subtypes
consensus clustering based
immune microenvironment characteristics
nomogram constructed based
key genes related
describe disease heterogeneity
related genes
key genes
consensus clustering
immune microenvironment
related pathways
jointly constructed
identified via
disease clustering
disease phenotypes
immune score
xylulose reductase
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study focused
study aimed
positively correlated
new clue
negatively correlated
learning algorithm
high enrichment
high accuracy
disease risk
diabetic nephropathy
control samples
cluster c2
cluster c1
clinical traits
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