Jason K. Yano

4.9k citations
29 papers · 3.6k indexed · 1 hit paper · h-index 20
Topics
Computational Drug Discovery Methods (11 papers)Pharmacogenetics and Drug Metabolism (11 papers)Drug Transport and Resistance Mechanisms (5 papers)

In The Last Decade

Jason K. Yano

27 papers receiving 3.5k citations

Hit Papers

The Structure of Human Microsomal Cytochrome P450 3A4 Det...20042026201120182004100200300400500

Peers

Jason K. Yano
Comparison fields: 5 of 115
  • Pharmacology 1.9k
  • Molecular Biology 1.6k
  • Computational Theory and Mathematics 1.1k
  • Oncology 1.0k
  • Organic Chemistry 466
Replace Emily E. Scott with:
Emily E. Scott United States
José Cosme France
Kenneth R. Korzekwa United States
Ken Korzekwa United States
Barry Jones United Kingdom
G. Schoch France
Deepak Dalvie United States
Michael R. Wester United States
Irina F. Sevrioukova United States
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Jason K. Yano relative to Emily E. Scott United States Emily E. Scott's profile →
Citations per field
00.5×1.5×1.9×
Emily E. Scott · 1×
Citations per year

Countries citing papers authored by Jason K. Yano

Since Specialization
Citations

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

Fields of papers citing papers by Jason K. Yano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jason K. Yano. 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 Jason K. Yano. The network helps show where Jason K. Yano may publish in the future.

Co-authorship network of co-authors of Jason K. Yano

This figure shows the co-authorship network connecting the top 25 collaborators of Jason K. Yano. A scholar is included among the top collaborators of Jason K. Yano 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 Jason K. Yano. Jason K. Yano is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 4
3 0
4 8
5 61
6 36
7 288
8 180
9 28
10 310
11 23
12 132
13 392
14 245
15
The Structure of Human Microsomal Cytochrome P450 3A4 Determined by X-ray Crystallography to 2.05-Å Resolutionbreakdown →
585
16 314
17 361
18 65
19 4
20 153

About Jason K. Yano

Jason K. Yano is a scholar working on Pharmacology, Computational Theory and Mathematics and Endocrinology, Diabetes and Metabolism, having authored 29 papers that have together received 3.6k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (11 papers), Pharmacogenetics and Drug Metabolism (11 papers) and Drug Transport and Resistance Mechanisms (5 papers). The work is most often cited by research in Pharmacology (1.9k citations), Computational Theory and Mathematics (1.1k citations) and Oncology (1.0k citations). Jason K. Yano has collaborated with scholars based in United States, Japan and Netherlands. Frequent co-authors include Eric F. Johnson, Keith J. Griffin, G. Schoch, Michael R. Wester, C.D. Stout, C.D. Stout, Stefaan Sansen, T.L. Poulos, Kathleen Aertgeerts and Christine Yang. Their work appears in journals such as Nature, Journal of Biological Chemistry and Scientific Reports.

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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