Cargando…
Addressing noise in co-expression network construction
Gene co-expression networks (GCNs) provide multiple benefits to molecular research including hypothesis generation and biomarker discovery. Transcriptome profiles serve as input for GCN construction and are derived from increasingly larger studies with samples across multiple experimental conditions...
Autores principales: | Burns, Joshua J R, Shealy, Benjamin T, Greer, Mitchell S, Hadish, John A, McGowan, Matthew T, Biggs, Tyler, Smith, Melissa C, Feltus, F Alex, Ficklin, Stephen P |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8769892/ https://www.ncbi.nlm.nih.gov/pubmed/34850822 http://dx.doi.org/10.1093/bib/bbab495 |
Ejemplares similares
-
Mutational signature assignment heterogeneity is widespread and can be addressed by ensemble approaches
por: Wu, Andy J, et al.
Publicado: (2023) -
MATTE: a pipeline of transcriptome module alignment for anti-noise phenotype-gene-related analysis
por: Cai, Guoxin, et al.
Publicado: (2023) -
McAN: a novel computational algorithm and platform for constructing and visualizing haplotype networks
por: Li, Lun, et al.
Publicado: (2023) -
New insights on human essential genes based on integrated analysis and the construction of the HEGIAP web-based platform
por: Chen, Hebing, et al.
Publicado: (2019) -
TSSFinder—fast and accurate ab initio prediction of the core promoter in eukaryotic genomes
por: de Medeiros Oliveira, Mauro, et al.
Publicado: (2021)