Joan Li

1.1k citations
20 papers · 689 · h-index 9

Impact in

Papers in

    • Renal and related cancers 6
    • Tissue Engineering and Regenerative Medicine 4
    • Pancreatic function and diabetes 1

Joan Li

19 papers receiving 669 citations

Peers

Joan Li
Comparison fields: 5 of 74
  • Genetics 152
  • Ophthalmology 108
  • Surgery 284
  • Radiology, Nuclear Medicine and Imaging 129
  • Cardiology and Cardiovascular Medicine 125
Replace Wei� Jin with:
Wei� Jin China
Shengshou Hu China
Kevin Hyman United States
George Paterakis Greece
Jorge L. Eller United States
N. Kipshidze United States
Th. Stegmann Germany
Alfonso L. Sabater United States
Jorge Bartolucci Chile
Mario Tombolini Italy
Joan Li relative to Wei� Jin China Wei� Jin's profile →
Citations per field
00.5×3.7×
Wei� Jin · 1×
Citations per year

Countries citing papers authored by Joan Li

Since Specialization
Citations

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

Fields of papers citing papers by Joan Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 2011298
2 2002153
3 201195
4 201628
5 201426
6 201920
7 201815
8 200512
9 20119
10 20128
11 20198
12 20186
13 20204
14 20212
15 20241
16 20251
17 20251
18 20231
19 20221
20 20230

About Joan Li

Joan Li is a scholar working on Molecular Biology, Surgery, Genetics, Cardiology and Cardiovascular Medicine and Pharmacology, having authored 20 papers that have together received 689 indexed citations. Recurring topics across this work include Renal and related cancers (6 papers), Mesenchymal stem cell research (4 papers), Tissue Engineering and Regenerative Medicine (4 papers), Spine and Intervertebral Disc Pathology (2 papers), Birth, Development, and Health (2 papers), Pregnancy and preeclampsia studies (2 papers), Musculoskeletal pain and rehabilitation (2 papers) and Pancreatic function and diabetes (1 paper). The work is most often cited by research in Genetics (152 citations), Ophthalmology (108 citations), Surgery (284 citations), Radiology, Nuclear Medicine and Imaging (129 citations) and Cardiology and Cardiovascular Medicine (125 citations). Joan Li has collaborated with scholars based in Australia, United States and China. Frequent co-authors include George J. Florakis, Vashe Chandrakanthan, Richard P. Harvey, Melissa H. Little, William T. Pu, Owen W.J. Prall, Naisana S. Asli, Emily K. Colvin, Hans Zoellner and Corey Heffernan. Their work appears in journals such as Scientific Reports, Stem Cell Research, Stem Cells Translational Medicine, The Journal of Pathology and Journal of Visualized Experiments.

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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