Cargando…
Regulostat Inferelator: a novel network biology platform to uncover molecular devices that predetermine cellular response phenotypes
With the emergence of genome editing technologies and synthetic biology, it is now possible to engineer genetic circuits driving a cell's phenotypic response to a stressor. However, capturing a continuous response, rather than simply a binary ‘on’ or ‘off’ response, remains a bioengineering cha...
Autores principales: | Ung, Choong Yong, Ghanat Bari, Mehrab, Zhang, Cheng, Liang, Jingjing, Correia, Cristina, Li, Hu |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6698671/ https://www.ncbi.nlm.nih.gov/pubmed/31114928 http://dx.doi.org/10.1093/nar/gkz417 |
Ejemplares similares
-
NetDecoder: a network biology platform that decodes context-specific biological networks and gene activities
por: da Rocha, Edroaldo Lummertz, et al.
Publicado: (2016) -
The Inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo
por: Bonneau, Richard, et al.
Publicado: (2006) -
Machine Learning-Assisted Network Inference Approach to Identify a New Class of Genes that Coordinate the Functionality of Cancer Networks
por: Ghanat Bari, Mehrab, et al.
Publicado: (2017) -
Uncovering tissue-specific binding features from differential deep learning
por: Phuycharoen, Mike, et al.
Publicado: (2020) -
IMPLICON: an ultra-deep sequencing method to uncover DNA methylation at imprinted regions
por: Klobučar, Tajda, et al.
Publicado: (2020)