Emily E. Scott

84 papers receiving 3.9k citations

Peers

Emily E. Scott
Comparison fields: 5 of 118
  • Pharmacology 2.1k
  • Computational Theory and Mathematics 740
  • Cell Biology 626
  • Oncology 749
  • Endocrinology, Diabetes and Metabolism 442
Replace Dijana Matak‐Vinković with:
Dijana Matak‐Vinković United Kingdom
C.D. Stout United States
Irina F. Sevrioukova United States
Julian A. Peterson United States
Ronald E. White United States
Moshe Finel Finland
Sergey A. Usanov Belarus
Dmitri R. Davydov United States
Charles B. Kasper United States
Ken Korzekwa United States
Emily E. Scott relative to Dijana Matak‐Vinković United Kingdom Dijana Matak‐Vinković's profile →
Citations per field
00.5×3.8×
Dijana Matak‐Vinković · 1×
Citations per year

Countries citing papers authored by Emily E. Scott

Since Specialization
Citations

This map shows the geographic impact of Emily E. Scott'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 Emily E. Scott with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emily E. Scott more than expected).

Fields of papers citing papers by Emily E. Scott

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Emily E. Scott. 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 Emily E. Scott. The network helps show where Emily E. Scott may publish in the future.

Co-authors

The 25 scholars most cited alongside Emily E. Scott, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Emily E. Scott Line = papers co-authored together Emily E. Scott links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 89 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001311
2 2003299
3 2012277
4 2004255
5 2013231
6 2008178
7 1997140
8 2001129
9 2014103
10 200489
11 200183
12 201381
13 201081
14 200778
15 201267
16 201465
17 201765
18 201159
19 202152
20 201751

About Emily E. Scott

Emily E. Scott is a scholar working on Pharmacology, Molecular Biology, Oncology, Endocrinology, Diabetes and Metabolism and Computational Theory and Mathematics, having authored 89 papers that have together received 3.9k indexed citations. Recurring topics across this work include Pharmacogenetics and Drug Metabolism (65 papers), Computational Drug Discovery Methods (18 papers), Hormonal Regulation and Hypertension (17 papers), Drug Transport and Resistance Mechanisms (17 papers), Estrogen and related hormone effects (12 papers), Hormonal and reproductive studies (7 papers), Analytical Chemistry and Chromatography (7 papers) and Hemoglobin structure and function (6 papers). The work is most often cited by research in Pharmacology (2.1k citations), Computational Theory and Mathematics (740 citations), Cell Biology (626 citations), Oncology (749 citations) and Endocrinology, Diabetes and Metabolism (442 citations). Emily E. Scott has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Natasha M. DeVore, James R. Halpert, Quentin Gibson, John S. Olson, Patrick Porubsky, Eric F. Johnson, Mark A. White, You Ai He, Grażyna D. Szklarz and D. Fernando Estrada. Their work appears in journals such as Journal of Biological Chemistry, Drug Metabolism and Disposition, Archives of Biochemistry and Biophysics, The FASEB Journal and Biochemistry.

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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