Deciphering eukaryotic gene-regulatory logic with 100 million random promoters-Reference-Cited by-同舟云学术

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Deciphering eukaryotic gene-regulatory logic with 100 million random promoters

Published:2019-12-02 Issue:1 Volume:38 Page:56-65
ISSN:1087-0156
Container-title:Nature Biotechnology
language:en
Short-container-title:Nat Biotechnol

Author:

de Boer Carl G.^ORCID,Vaishnav Eeshit Dhaval^ORCID,Sadeh Ronen^ORCID,Abeyta Esteban Luis^ORCID,Friedman Nir^ORCID,Regev Aviv^ORCID

Funder

U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute

Massachusetts Institute of Technology

Israel Science Foundation

Howard Hughes Medical Institute

Publisher

Springer Science and Business Media LLC

Subject

Biomedical Engineering,Molecular Medicine,Applied Microbiology and Biotechnology,Bioengineering,Biotechnology

Link

http://www.nature.com/articles/s41587-019-0315-8.pdf

Reference62 articles.

1. Beer, M. A. & Tavazoie, S. Predicting gene expression from sequence. Cell 117, 185–198 (2004).

2. Yuan, Y., Guo, L., Shen, L. & Liu, J. S. Predicting gene expression from sequence: a reexamination. PLoS Comput. Biol. 3, e243 (2007).

3. Kinney, J. B., Murugan, A., Callan, C. G. Jr. & Cox, E. C. Using deep sequencing to characterize the biophysical mechanism of a transcriptional regulatory sequence. Proc. Natl Acad. Sci. USA107, 9158–9163 (2010).

4. van Arensbergen, J. et al. Genome-wide mapping of autonomous promoter activity in human cells. Nat. Biotechnol. 35, 145–153 (2017).

5. Muerdter, F. et al. Resolving systematic errors in widely used enhancer activity assays in human cells. Nat. Methods 15, 141–149 (2018).

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