Beijing Tan

16 papers receiving 434 citations

Peers

Beijing Tan
Comparison fields: 5 of 84
  • Pharmacology 115
  • Endocrinology, Diabetes and Metabolism 126
  • Safety Research 41
  • Spectroscopy 81
  • Analytical Chemistry 31
Replace James B. Mangold with:
James B. Mangold United States
Teresa Tam Canada
Thomas S. McDonald United States
Richard Fux Germany
Yasushi Yoshigae Japan
Carlo Sensenhauser United States
Setsuko Komuro Japan
Thierry Umbdenstock France
Vinayak Hosagrahara United States
Ryosei Kawai Japan
Beijing Tan relative to James B. Mangold United States James B. Mangold's profile →
Citations per field
00.5×2.7×
James B. Mangold · 1×
Citations per year

Countries citing papers authored by Beijing Tan

Since Specialization
Citations

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

Fields of papers citing papers by Beijing Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Beijing Tan. 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 Beijing Tan. The network helps show where Beijing Tan may publish in the future.

Co-authors

The 25 scholars most cited alongside Beijing Tan, 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 Beijing Tan Line = papers co-authored together Beijing Tan links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 201278
2 200071
3 201159
4 201345
5 201641
6 201335
7 201123
8 201219
9 201017
10 201114
11 200014
12 201113
13 200910
14
DETERMINING THE OPTIMAL DOSE OF MOXIDECTIN FOR ONCHOCERCIASIS VIA PHARMACOKINETIC-PHARMACODYNAMIC (PK-PD) MODELLING OF DATA FROM HEALTHY VOLUNTEERS AND PATIENTS WITH ONCHOCERCIASIS
20173
15 20202
16 20001

About Beijing Tan

Beijing Tan is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism, Pharmacology, Pharmacology and Spectroscopy, having authored 16 papers that have together received 445 indexed citations. Recurring topics across this work include Diabetes Treatment and Management (4 papers), Pharmacogenetics and Drug Metabolism (3 papers), Antibiotics Pharmacokinetics and Efficacy (2 papers), Receptor Mechanisms and Signaling (2 papers), Cellular Mechanics and Interactions (2 papers), thermodynamics and calorimetric analyses (2 papers), Drug Transport and Resistance Mechanisms (2 papers) and Advanced Chemical Sensor Technologies (1 paper). The work is most often cited by research in Pharmacology (115 citations), Endocrinology, Diabetes and Metabolism (126 citations), Safety Research (41 citations), Spectroscopy (81 citations) and Analytical Chemistry (31 citations). Beijing Tan has collaborated with scholars based in United States. Frequent co-authors include James K. Hardy, Karen Atkinson, Thomas S. McDonald, R. Scott Obach, Li Di, Larry M. Tremaine, Yi‐An Bi, Patrick Trapa, Angela Wolford and Yurong Lai. Their work appears in journals such as Bioorganic & Medicinal Chemistry Letters, Drug Metabolism and Disposition, AAPS PharmSciTech, Diabetes Obesity and Metabolism and American Journal of Physiology-Endocrinology and Metabolism.

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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