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Items: 3

1.

Iterative deep learning-design of human enhancers exploits condensed sequence grammar to achieve cell type-specificity [RNA-Seq]

(Submitter supplied) An important and largely unsolved problem in synthetic biology is how to target gene expression to specific cell types. Here, we apply iterative deep learning to design synthetic enhancers with strong differential activity between two human cell lines. We initially train models on published datasets of enhancer activity and chromatin accessibility and use them to guide the design of synthetic enhancers that maximize predicted specificity. more...
Organism:
Homo sapiens; synthetic construct
Type:
Expression profiling by high throughput sequencing; Other
Platforms:
GPL27609 GPL21697
16 Samples
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Series
Accession:
GSE269036
ID:
200269036
2.

NextSeq 550 (synthetic construct)

Organism:
synthetic construct
28 Series
593 Samples
Download data
Platform
Accession:
GPL27609
ID:
100027609
3.

R1-MPRA_DNA

Organism:
synthetic construct
Source name:
n/a
Platform:
GPL27609
Series:
GSE269036
Download data
Sample
Accession:
GSM8305405
ID:
308305405
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