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Ying Hefner

As seen in: PNAS, BMC Systems Biology, BioRxiv, eLife
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Articles

Interpreting roles of mutations associated with the emergence of S. aureus USA300 strains using transcriptional regulatory network reconstruction

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By Saugat Poudel, Jason Hyun, Ying Hefner, Jon Monk
| eLife
Request a detailed protocol ICA of RNA-sequencing data was performed using the pymodulon package (Sastry et al., 2021). Using the package, all available RNA-sequencing data for non-USA300 and USA300 strains were downloaded, run through the QC/QA pipeline, manually curated for metadata and aligned to the TCH1516 genome (NC_010079, NC_012417, and NC_010063).
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Interpreting roles of mutations associated with the emergence of S. aureus USA300 strains using transcriptional regulatory network reconstruction

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By Saugat Poudel, Jason Hyun, Ying Hefner, Jonathan Monk
| BioRxiv
Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website.
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Reconstructing the Transcriptional Regulatory Network of Probiotic L. reuteri is Enabled by Transcriptomics and Machine Learning

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By Akanksha Rajput, Ying Hefner, Richard Szubin, Jonathan Josephs-Spaulding
| BioRxiv
New Results doi: https://doi.org/10.1101/2023.07.03.547516 Abstract Limosilactobacillus reuteri, a probiotic microbe instrumental to human health and sustainable food production, adapts to diverse environmental shifts via dynamic gene expression. We applied independent component analysis to 117 high-quality RNA-seq datasets to decode its transcriptional regulatory network (TRN), identifying 35 distinct signals that modulate specific gene sets. This study uncovers the fundamental properties of L.
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