Cargando…
Assessing key decisions for transcriptomic data integration in biochemical networks
To gain insights into complex biological processes, genome-scale data (e.g., RNA-Seq) are often overlaid on biochemical networks. However, many networks do not have a one-to-one relationship between genes and network edges, due to the existence of isozymes and protein complexes. Therefore, decisions...
Autores principales: | Richelle, Anne, Joshi, Chintan, Lewis, Nathan E. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6668847/ https://www.ncbi.nlm.nih.gov/pubmed/31323017 http://dx.doi.org/10.1371/journal.pcbi.1007185 |
Ejemplares similares
-
StanDep: Capturing transcriptomic variability improves context-specific metabolic models
por: Joshi, Chintan J., et al.
Publicado: (2020) -
Correction: StanDep: Capturing transcriptomic variability improves context-specific metabolic models
por: Joshi, Chintan J., et al.
Publicado: (2022) -
Increasing consensus of context-specific metabolic models by integrating data-inferred cell functions
por: Richelle, Anne, et al.
Publicado: (2019) -
Integration of transcriptomic data identifies key hallmark genes in hypertrophic cardiomyopathy
por: Xu, Jing, et al.
Publicado: (2021) -
Model-based assessment of mammalian cell metabolic functionalities using omics data
por: Richelle, Anne, et al.
Publicado: (2021)