Graphical Abstract.

Graphical Abstract.

<p>The first box shows how the COPD and the Differential partial correlation networks have been built. Given a source of biological information, such as a PPI network or set of functional annotations, for every gene i and j (g<sub>i</sub>,g<sub>j</sub>) we extract the g...

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Bibliographic Details
Main Author: Michele Gentili (19865208) (author)
Other Authors: Kimberly Glass (416881) (author), Enrico Maiorino (6956657) (author), Brian D. Hobbs (5118383) (author), Zhonghui Xu (659900) (author), Peter J. Castaldi (8788598) (author), Michael H. Cho (6856079) (author), Craig P. Hersh (8543712) (author), Dandi Qiao (5118380) (author), Jarrett D. Morrow (3082395) (author), Vincent J. Carey (19865211) (author), John Platig (3115692) (author), Edwin K. Silverman (6856082) (author)
Published: 2024
Subjects:
Microbiology
Cell Biology
Genetics
Molecular Biology
Science Policy
Biological Sciences not elsewhere classified
established environmental exposures
complex disease influenced
(~ 70mb ),
4q region bounded
identified several co
copd genetic susceptibility
partial correlations informed
including signals near
div >< p
genes differentially co
copd vs controls
partial correlations
region enriched
genomic region
differential co
copd genome
copd cases
upon clustering
tet2 </
tet2 )</
spp1 </
seq data
regional cluster
previously implicated
ppm1k </
ppa2 </
lung tissue
leveraging rna
hhip </
gstcd </
fam13a </
cigarette smoking
btc </
based knock
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