Bing V. Li

16 papers receiving 316 citations

Peers

Bing V. Li
Comparison fields: 5 of 74
  • Pharmaceutical Science 103
  • Statistics and Probability 52
  • Pulmonary and Respiratory Medicine 205
  • Pediatrics, Perinatology and Child Health 59
  • Physiology 75
Replace David Christopher with:
David Christopher United States
Bhawana Saluja United States
Jens Markus Borghardt Germany
Renishkumar Delvadia United States
Anders Källén Sweden
Hiroyuki Yoshida Japan
Pär Ewing Sweden
Gustavo Mendes Lima Santos Brazil
Sebastiaan C. Goulooze Netherlands
K.P. Steed United Kingdom
Bing V. Li relative to David Christopher United States David Christopher's profile →
Citations per field
00.5×2.7×
David Christopher · 1×
Citations per year

Countries citing papers authored by Bing V. Li

Since Specialization
Citations

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

Fields of papers citing papers by Bing V. Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bing V. Li. 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 Bing V. Li. The network helps show where Bing V. Li may publish in the future.

Co-authors

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

All Works

16 of 16 papers shown
#Work
1 200965
2 201546
3 201543
4 201443
5 201332
6 201917
7 202212
8 201311
9 202211
10 202211
11 201410
12 20169
13 20148
14 20237
15 20242
16 20121

About Bing V. Li

Bing V. Li is a scholar working on Pulmonary and Respiratory Medicine, Pharmaceutical Science, Pediatrics, Perinatology and Child Health, Physiology and Statistics and Probability, having authored 16 papers that have together received 328 indexed citations. Recurring topics across this work include Inhalation and Respiratory Drug Delivery (9 papers), Drug Solubulity and Delivery Systems (5 papers), Pharmaceutical studies and practices (5 papers), Asthma and respiratory diseases (4 papers), Statistical Methods in Clinical Trials (3 papers), Protein purification and stability (2 papers), Biosimilars and Bioanalytical Methods (2 papers) and Cyclone Separators and Fluid Dynamics (2 papers). The work is most often cited by research in Pharmaceutical Science (103 citations), Statistics and Probability (52 citations), Pulmonary and Respiratory Medicine (205 citations), Pediatrics, Perinatology and Child Health (59 citations) and Physiology (75 citations). Bing V. Li has collaborated with scholars based in United States, Sweden and Thailand. Frequent co-authors include Lawrence X. Yu, Dale P. Conner, Badrul A. Chowdhury, Wallace P. Adams, Sau L. Lee, Sau Lawrence Lee, Robert Lionberger, Ben Forbes, David Christopher and Myrna Dolovich. Their work appears in journals such as The AAPS Journal, CPT Pharmacometrics & Systems Pharmacology, Advanced Drug Delivery Reviews, Journal of Pharmaceutical Sciences and AAPS PharmSciTech.

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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