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Joslynn S. Lee

Researcher at University of Minnesota

Publications -  15
Citations -  10176

Joslynn S. Lee is an academic researcher from University of Minnesota. The author has contributed to research in topics: Structural genomics & Gene expression. The author has an hindex of 8, co-authored 13 publications receiving 4369 citations. Previous affiliations of Joslynn S. Lee include Northeastern University & Howard Hughes Medical Institute.

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Journal ArticleDOI

Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

Evan Bolyen, +123 more
- 01 Aug 2019 - 
TL;DR: QIIME 2 development was primarily funded by NSF Awards 1565100 to J.G.C. and R.K.P. and partial support was also provided by the following: grants NIH U54CA143925 and U54MD012388.
Posted ContentDOI

QIIME 2: Reproducible, interactive, scalable, and extensible microbiome data science

Evan Bolyen, +119 more
- 24 Oct 2018 - 
TL;DR: QIIME 2 provides new features that will drive the next generation of microbiome research, including interactive spatial and temporal analysis and visualization tools, support for metabolomics and shotgun metagenomics analysis, and automated data provenance tracking to ensure reproducible, transparent microbiome data science.
Journal ArticleDOI

Author Correction: Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.

Evan Bolyen, +125 more
- 01 Sep 2019 - 
TL;DR: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Journal ArticleDOI

Beyond antioxidant genes in the ancient Nrf2 regulatory network

TL;DR: Interestingly, the ancient network also highlights a prominent negative feedback loop; this, combined with the finding that Nrf2-mediated regulatory output is tightly linked to the quality of the ARE it is targeting, suggests that precise regulation of nuclear NRF2 concentration is necessary to achieve proper quantitative regulation of distinct gene sets.
Journal ArticleDOI

DNA-binding sequence specificity of DUX4

TL;DR: By multimerizing binding sites, this work finds that DUX4 transcriptional activation demonstrates tremendous synergy and that at low DNA concentrations, at least two motifs are necessary to detect a transcriptional response.