 Connection
Scott Auerbach to Transcriptome
This is a "connection" page, showing publications Scott Auerbach has written about Transcriptome.
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Connection Strength |
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1.045 |
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Carberry CK, Hartwell H, Rider CV, Wheeler MW, Auerbach SS, Rager JE. Extracellular Vesicle (EV) Mechanisms of Toxicity for Per and Polyfluoroalkyl Substances: Comparing Transcriptomic Points of Departure Across Global Versus EV Regulatory Gene Sets. Environ Mol Mutagen. 2025 Mar; 66(3):99-121.
Score: 0.148
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O'Brien J, Mitchell C, Auerbach S, Doonan L, Ewald J, Everett L, Faranda A, Johnson K, Reardon A, Rooney J, Shao K, Stainforth R, Wheeler M, Dalmas Wilk D, Williams A, Yauk C, Costa E. Bioinformatic workflows for deriving transcriptomic points of departure: current status, data gaps, and research priorities. Toxicol Sci. 2025 Feb 01; 203(2):147-159.
Score: 0.147
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Johnson KJ, Auerbach SS, Stevens T, Barton-Maclaren TS, Costa E, Currie RA, Dalmas Wilk D, Haq S, Rager JE, Reardon AJF, Wehmas L, Williams A, O'Brien J, Yauk C, LaRocca JL, Pettit S. A Transformative Vision for an Omics-Based Regulatory Chemical Testing Paradigm. Toxicol Sci. 2022 11 23; 190(2):127-132.
Score: 0.126
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Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, Beger RD, Bouhifd M, O'Brien J, Burgoon L, Caiment F, Carpi D, Chen T, Chorley BN, Colbourne J, Corvi R, Debrauwer L, O'Donovan C, Ebbels TMD, Ekman DR, Faulhammer F, Gribaldo L, Hilton GM, Jones SP, Kende A, Lawson TN, Leite SB, Leonards PEG, Luijten M, Martin A, Moussa L, Rudaz S, Schmitz O, Sobanski T, Strauss V, Vaccari M, Vijay V, Weber RJM, Williams AJ, Williams A, Thomas RS, Whelan M. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol. 2021 Oct; 125:105020.
Score: 0.115
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Crizer DM, Ramaiahgari SC, Ferguson SS, Rice JR, Dunlap PE, Sipes NS, Auerbach SS, Merrick BA, DeVito MJ. Benchmark Concentrations for Untargeted Metabolomics Versus Transcriptomics for Liver Injury Compounds in In Vitro Liver Models. Toxicol Sci. 2021 05 27; 181(2):175-186.
Score: 0.114
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Gwinn WM, Auerbach SS, Parham F, Stout MD, Waidyanatha S, Mutlu E, Collins B, Paules RS, Merrick BA, Ferguson S, Ramaiahgari S, Bucher JR, Sparrow B, Toy H, Gorospe J, Machesky N, Shah RR, Balik-Meisner MR, Mav D, Phadke DP, Roberts G, DeVito MJ. Evaluation of 5-day In Vivo Rat Liver and Kidney With High-throughput Transcriptomics for Estimating Benchmark Doses of Apical Outcomes. Toxicol Sci. 2020 08 01; 176(2):343-354.
Score: 0.107
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Johnson KJ, Auerbach SS, Costa E. A Rat Liver Transcriptomic Point of Departure Predicts a Prospective Liver or Non-liver Apical Point of Departure. Toxicol Sci. 2020 07 01; 176(1):86-102.
Score: 0.107
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Gong B, Wang C, Su Z, Hong H, Thierry-Mieg J, Thierry-Mieg D, Shi L, Auerbach SS, Tong W, Xu J. Transcriptomic profiling of rat liver samples in a comprehensive study design by RNA-Seq. Sci Data. 2014; 1:140021.
Score: 0.071
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Merrick BA, Phadke DP, Auerbach SS, Mav D, Stiegelmeyer SM, Shah RR, Tice RR. RNA-Seq profiling reveals novel hepatic gene expression pattern in aflatoxin B1 treated rats. PLoS One. 2013; 8(4):e61768.
Score: 0.065
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Mav D, Shah RR, Howard BE, Auerbach SS, Bushel PR, Collins JB, Gerhold DL, Judson RS, Karmaus AL, Maull EA, Mendrick DL, Merrick BA, Sipes NS, Svoboda D, Paules RS. A hybrid gene selection approach to create the S1500+ targeted gene sets for use in high-throughput transcriptomics. PLoS One. 2018; 13(2):e0191105.
Score: 0.023
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Rager JE, Auerbach SS, Chappell GA, Martin E, Thompson CM, Fry RC. Benchmark Dose Modeling Estimates of the Concentrations of Inorganic Arsenic That Induce Changes to the Neonatal Transcriptome, Proteome, and Epigenome in a Pregnancy Cohort. Chem Res Toxicol. 2017 10 16; 30(10):1911-1920.
Score: 0.022
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Connection Strength
The connection strength for concepts is the sum of the scores for each matching publication.
Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
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