Multi-omic data integration enables discovery of hidden biological regularities
Translating omics data sets into biological insight is one of the great challenges of our time. Here, the authors make headway by synchronising pairs of omics data types via invariants across conditions and by integrating datasets into a genome-scale model of E. coli metabolism and gene expression.
Guardado en:
Autores principales: | Ali Ebrahim, Elizabeth Brunk, Justin Tan, Edward J. O'Brien, Donghyuk Kim, Richard Szubin, Joshua A. Lerman, Anna Lechner, Anand Sastry, Aarash Bordbar, Adam M. Feist, Bernhard O. Palsson |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2016
|
Materias: | |
Acceso en línea: | https://doaj.org/article/54b0e226f9794904895aa0e7518d169f |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Evolution of gene knockout strains of E. coli reveal regulatory architectures governed by metabolism
por: Douglas McCloskey, et al.
Publicado: (2018) -
The Escherichia coli transcriptome mostly consists of independently regulated modules
por: Anand V. Sastry, et al.
Publicado: (2019) -
Machine learning uncovers independently regulated modules in the Bacillus subtilis transcriptome
por: Kevin Rychel, et al.
Publicado: (2020) -
Revealing genome-scale transcriptional regulatory landscape of OmpR highlights its expanded regulatory roles under osmotic stress in Escherichia coli K-12 MG1655
por: Sang Woo Seo, et al.
Publicado: (2017) -
Elucidation of Regulatory Modes for Five Two-Component Systems in <named-content content-type="genus-species">Escherichia coli</named-content> Reveals Novel Relationships
por: Kumari Sonal Choudhary, et al.
Publicado: (2020)