Erica J. Reschly

1.3k total citations
17 papers, 1.1k citations indexed

About

Erica J. Reschly is a scholar working on Genetics, Endocrinology, Diabetes and Metabolism and Pharmacology. According to data from OpenAlex, Erica J. Reschly has authored 17 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Genetics, 7 papers in Endocrinology, Diabetes and Metabolism and 6 papers in Pharmacology. Recurrent topics in Erica J. Reschly's work include Estrogen and related hormone effects (9 papers), Pharmacogenetics and Drug Metabolism (6 papers) and Hormonal Regulation and Hypertension (6 papers). Erica J. Reschly is often cited by papers focused on Estrogen and related hormone effects (9 papers), Pharmacogenetics and Drug Metabolism (6 papers) and Hormonal Regulation and Hypertension (6 papers). Erica J. Reschly collaborates with scholars based in United States, United Kingdom and Slovakia. Erica J. Reschly's co-authors include Matthew D. Krasowski, Sean Ekins, Lee R. Hagey, Ni Ai, Manisha Iyer, William J. Welsh, Peter W. Swaan, Michael Sinz, Sandhya Kortagere and Sridhar Mani and has published in prestigious journals such as Journal of Biological Chemistry, Blood and Environmental Health Perspectives.

In The Last Decade

Erica J. Reschly

17 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Erica J. Reschly United States 17 413 337 248 202 197 17 1.1k
Bruce Wisely United States 10 532 1.3× 353 1.0× 350 1.4× 339 1.7× 245 1.2× 11 1.2k
Susumu Kodama Japan 19 403 1.0× 445 1.3× 256 1.0× 223 1.1× 329 1.7× 34 1.1k
Jaspreet S. Sidhu United States 21 879 2.1× 476 1.4× 139 0.6× 256 1.3× 126 0.6× 34 1.6k
Paul J. Ciaccio United States 18 740 1.8× 236 0.7× 114 0.5× 262 1.3× 79 0.4× 29 1.3k
Graham P. Hayhurst United Kingdom 16 846 2.0× 371 1.1× 245 1.0× 497 2.5× 159 0.8× 19 1.9k
Tomoya Yamada Japan 23 501 1.2× 266 0.8× 256 1.0× 156 0.8× 295 1.5× 71 1.5k
Craig B. Marcus United States 22 542 1.3× 416 1.2× 183 0.7× 205 1.0× 97 0.5× 51 1.4k
Meishu Xu United States 25 518 1.3× 243 0.7× 192 0.8× 268 1.3× 259 1.3× 50 1.4k
Bryan Mackowiak United States 15 425 1.0× 206 0.6× 92 0.4× 108 0.5× 159 0.8× 29 1.1k
Jeremy Mills United Kingdom 17 432 1.0× 209 0.6× 112 0.5× 223 1.1× 81 0.4× 47 1.1k

Countries citing papers authored by Erica J. Reschly

Since Specialization
Citations

This map shows the geographic impact of Erica J. Reschly's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Erica J. Reschly with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Erica J. Reschly more than expected).

Fields of papers citing papers by Erica J. Reschly

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Erica J. Reschly. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Erica J. Reschly. The network helps show where Erica J. Reschly may publish in the future.

Co-authorship network of co-authors of Erica J. Reschly

This figure shows the co-authorship network connecting the top 25 collaborators of Erica J. Reschly. A scholar is included among the top collaborators of Erica J. Reschly based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Erica J. Reschly. Erica J. Reschly is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
1.
Fidler, Andrew E., Patrick T. Holland, Erica J. Reschly, Sean Ekins, & Matthew D. Krasowski. (2011). Activation of a tunicate (Ciona intestinalis) xenobiotic receptor orthologue by both natural toxins and synthetic toxicants. Toxicon. 59(2). 365–372. 25 indexed citations
2.
Krasowski, Matthew D., Ni Ai, Lee R. Hagey, et al.. (2011). The evolution of farnesoid X, vitamin D, and pregnane X receptors: insights from the green-spotted pufferfish (Tetraodon nigriviridis) and other non-mammalian species. BMC Biochemistry. 12(1). 5–5. 35 indexed citations
3.
Kortagere, Sandhya, Matthew D. Krasowski, Erica J. Reschly, et al.. (2010). Evaluation of Computational Docking to Identify Pregnane X Receptor Agonists in the ToxCast Database. Environmental Health Perspectives. 118(10). 1412–1417. 29 indexed citations
4.
Ekins, Sean, Sandhya Kortagere, Manisha Iyer, et al.. (2009). Challenges Predicting Ligand-Receptor Interactions of Promiscuous Proteins: The Nuclear Receptor PXR. PLoS Computational Biology. 5(12). e1000594–e1000594. 93 indexed citations
5.
Reschly, Erica J., Ni Ai, Sean Ekins, et al.. (2008). Evolution of the bile salt nuclear receptor FXR in vertebrates*. Journal of Lipid Research. 49(7). 1577–1587. 92 indexed citations
6.
Reschly, Erica J., Ni Ai, William J. Welsh, et al.. (2008). Ligand specificity and evolution of liver X receptors. The Journal of Steroid Biochemistry and Molecular Biology. 110(1-2). 83–94. 56 indexed citations
7.
Ekins, Sean, Erica J. Reschly, Lee R. Hagey, & Matthew D. Krasowski. (2008). Evolution of pharmacologic specificity in the pregnane X receptor. BMC Evolutionary Biology. 8(1). 103–103. 93 indexed citations
8.
Krasowski, Matthew D., Erica J. Reschly, & Sean Ekins. (2008). Intrinsic Disorder in Nuclear Hormone Receptors. Journal of Proteome Research. 7(10). 4359–4372. 57 indexed citations
9.
Khandelwal, Akash, Matthew D. Krasowski, Erica J. Reschly, et al.. (2008). Machine Learning Methods and Docking for Predicting Human Pregnane X Receptor Activation. Chemical Research in Toxicology. 21(7). 1457–1467. 62 indexed citations
10.
Reschly, Erica J., Afonso Celso Dias Bainy, Jacó Joaquim Mattos, et al.. (2007). Functional evolution of the vitamin D and pregnane X receptors. BMC Evolutionary Biology. 7(1). 222–222. 82 indexed citations
11.
Ekins, Sean, Cheng Chang, Sridhar Mani, et al.. (2007). Human Pregnane X Receptor Antagonists and Agonists Define Molecular Requirements for Different Binding Sites. Molecular Pharmacology. 72(3). 592–603. 123 indexed citations
12.
Spaulding, Christina, Erica J. Reschly, Yumi Yashiro–Ohtani, et al.. (2007). Notch1 co-opts lymphoid enhancer factor 1 for survival of murine T-cell lymphomas. Blood. 110(7). 2650–2658. 40 indexed citations
13.
Reschly, Erica J., Christina Spaulding, Tomas Vilimas, et al.. (2006). Notch1 promotes survival of E2A-deficient T cell lymphomas through pre–T cell receptor–dependent and –independent mechanisms. Blood. 107(10). 4115–4121. 43 indexed citations
14.
Iyer, Manisha, Erica J. Reschly, & Matthew D. Krasowski. (2006). Functional evolution of the pregnane X receptor. Expert Opinion on Drug Metabolism & Toxicology. 2(3). 381–397. 37 indexed citations
15.
Reschly, Erica J. & Matthew D. Krasowski. (2006). Evolution and Function of the NR1I Nuclear Hormone Receptor Subfamily (VDR, PXR, and CAR) with Respect to Metabolism of Xenobiotics and Endogenous Compounds. Current Drug Metabolism. 7(4). 349–365. 109 indexed citations
16.
Reschly, Erica J., Mary G. Sorci‐Thomas, W. Sean Davidson, et al.. (2002). Apolipoprotein A-I α-Helices 7 and 8 Modulate High Density Lipoprotein Subclass Distribution. Journal of Biological Chemistry. 277(12). 9645–9654. 36 indexed citations
17.
Baum, Charles L., et al.. (1997). Sterol Carrier Protein-2 Overexpression Enhances Sterol Cycling and Inhibits Cholesterol Ester Synthesis and High Density Lipoprotein Cholesterol Secretion. Journal of Biological Chemistry. 272(10). 6490–6498. 62 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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