R
Ronald C. Taylor
Researcher at Pacific Northwest National Laboratory
Publications - 66
Citations - 7299
Ronald C. Taylor is an academic researcher from Pacific Northwest National Laboratory. The author has contributed to research in topics: Biological network inference & Gene. The author has an hindex of 24, co-authored 65 publications receiving 6847 citations. Previous affiliations of Ronald C. Taylor include United States Department of Energy & Vanderbilt University.
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Journal ArticleDOI
Network inference algorithms elucidate Nrf2 regulation of mouse lung oxidative stress.
TL;DR: This work shows the promise of network inference algorithms operating on high-throughput gene expression data in identifying transcriptional regulatory and other signaling relationships implicated in mammalian disease.
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The frameshift signal of HIV-1 involves a potential intramolecular triplex RNA structure
Jonathan D. Dinman,Sara N. Richter,Ewan P. Plant,Ronald C. Taylor,Amy B. Hammell,Tariq M. Rana +5 more
TL;DR: It is suggested that the potential intramolecular triplex structure is essential for viral propagation and viability, and that small molecules targeted to this RNA structure may possess antiretroviral activities.
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Microbial Community Metabolic Modeling: A Community Data-Driven Network Reconstruction
Christopher S. Henry,Hans C. Bernstein,Pamela Weisenhorn,Ronald C. Taylor,Joon-Yong Lee,Jeremy Zucker,Hyun-Seob Song +6 more
TL;DR: This method focuses on directly predicting interspecies metabolic interactions in a community, when axenic information is insufficient, and validated through the case study of a bacterial photoautotroph–heterotroph consortium that was used to provide data needed for a community‐level metabolic network reconstruction.
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Reverse engineering adverse outcome pathways
Edward J. Perkins,J. Kevin Chipman,Stephen W. Edwards,Tanwir Habib,Francesco Falciani,Ronald C. Taylor,Graham van Aggelen,Chris D. Vulpe,Philipp Antczak,Alexandre Loguinov +9 more
TL;DR: R reverse engineering complex interaction networks from high dimensional omics data allows for formation of testable hypotheses about key biological processes, biomarkers, or alternative endpoints that can be used to monitor an AOP, and the unique challenges facing the application of this approach in ecotoxicology were identified.
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GEST: a gene expression search tool based on a novel Bayesian similarity metric.
TL;DR: A similarity metric for gene expression array experiments that takes into account the complex joint distribution of expression values is presented, a computationally tractable approximation to this measure is provided, and a database search tool is implemented based on it.