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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An Integrated Database to Support Research on Escherichia Coli
A. Baehr,G. Dunham,Hideo Matsuda,G.S. Michaels,Ronald C. Taylor,Ross Overbeek,K.E. Rudd,A. Ginsburg,D. Joerg,T. Kazic,Ray Hagstrom,D. Zawada,C. Smith,Kaoru Yoshida +13 more
TL;DR: The present system, combined with a tutorial manual, provides immediate access to the integrated knowledge base for E. coli chromosome data and serves as the foundation for development of more user-friendly interfaces that have the same retrieval power and high-level tools to analyze complex chromosome organization.
Journal ArticleDOI
A Network Inference Workflow Applied to Virulence-Related Processes in Salmonella typhimurium
Ronald C. Taylor,Mudita Singhal,Jennifer B. Weller,Saeed Khoshnevis,Liang Shi,Jason E. McDermott +5 more
TL;DR: A workflow for the reconstruction of parts of the transcriptional regulatory network of the pathogenic bacterium Salmonella typhimurium based on the information contained in sets of microarray gene‐expression data now available for that organism is discussed.
Journal Article
Toward a Human Genome Encyclopedia.
Kaoru Yoshida,Cassandra L. Smith,Toni Kazic,George S. Michaels,Ronald C. Taylor,David Zawada,Ray Hagstrom,Ross Overbeek +7 more
Book ChapterDOI
Metabolic Network Modeling for Computer‐Aided Design of Microbial Interactions
Hyun-Seob Song,William C. Nelson,Joon-Yong Lee,Ronald C. Taylor,Christopher S. Henry,Alexander S. Beliaev,Doraiswami Ramkrishna,Hans C. Bernstein,Hans C. Bernstein +8 more
TL;DR: Predictive in silico tools such as metabolic network modeling are essential for the rational design of controllable microbial interactions.
Journal ArticleDOI
Computing and Applying Atomic Regulons to Understand Gene Expression and Regulation
José P. Faria,James J. Davis,Janaka N. Edirisinghe,Janaka N. Edirisinghe,Ronald C. Taylor,Pamela Weisenhorn,Robert Olson,Robert Olson,Rick Stevens,Miguel Rocha,Isabel Rocha,Aaron A. Best,Matthew DeJongh,Nathan L. Tintle,Bruce Parrello,Ross Overbeek,Christopher S. Henry +16 more
TL;DR: An approach for inferring ARs that leverages large-scale expression data sets, gene context, and functional relationships among genes is described and it is determined that while more data improve ARs, it is not necessary to use the full set of gene expression experiments available to produce high quality ARs.