Wan-Jin Lu
Impact in
Papers in
-
- Single-cell and spatial transcriptomics 10
- Hedgehog Signaling Pathway Studies 5
- Cell death mechanisms and regulation 3
- Bone Metabolism and Diseases 2
- Genetics 4
- Mesenchymal stem cell research 4
- Co-authors
- John Abrams (8 shared papers)James F. Amatruda (1 shared paper)Philip A. Beachy (5 shared papers)Joseph A. Chapo (1 shared paper)Ignasi Roig (1 shared paper)Su Kit Chew (1 shared paper)Antony Rodriguez (1 shared paper)Sharad Kumar (1 shared paper)
- Journals
- Nature (5 papers)Science (3 papers)Cell (3 papers)Proceedings of the National Academy of Sciences (3 papers)Nature Communications (2 papers)
- Partner nations
- United StatesChinaSouth Korea
In The Last Decade
Wan-Jin Lu
30 papers receiving 4.1k citations
Wan-Jin Lu's Hit Papers
Peers
Comparison fields: 5 of 113
- Aging 455
- Genetics 485
- Molecular Biology 2.1k
- Rheumatology 198
- Physiology 363
Countries citing papers authored by Wan-Jin Lu
This map shows the geographic impact of Wan-Jin Lu'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 Wan-Jin Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wan-Jin Lu more than expected).
Fields of papers citing papers by Wan-Jin Lu
This network shows the impact of papers produced by Wan-Jin Lu. 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 Wan-Jin Lu. The network helps show where Wan-Jin Lu may publish in the future.
Co-authors
The 25 scholars most cited alongside Wan-Jin Lu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A single-cell transcriptomic atlas characterizes ageing tissues in the mouse Hit paper breakdown → | 2020 | 828 |
| 2 | The Tabula Sapiens: A multiple-organ, single-cell transcriptomic atlas of humans Hit paper breakdown → | 2022 | 738 |
| 3 | Identification and Specification of the Mouse Skeletal Stem Cell Hit paper breakdown → | 2015 | 598 |
| 4 | Identification of the Human Skeletal Stem Cell Hit paper breakdown → | 2018 | 475 |
| 5 | Ageing hallmarks exhibit organ-specific temporal signatures Hit paper breakdown → | 2020 | 473 |
| 6 | 2004 | 133 | |
| 7 | 2022 | 112 | |
| 8 | 2009 | 90 | |
| 9 | 2010 | 75 | |
| 10 | 2022 | 73 | |
| 11 | 2016 | 70 | |
| 12 | 2021 | 57 | |
| 13 | 2017 | 51 | |
| 14 | 2014 | 49 | |
| 15 | 2008 | 46 | |
| 16 | 2007 | 45 | |
| 17 | 2006 | 42 | |
| 18 | 2017 | 40 | |
| 19 | 2022 | 33 | |
| 20 | 2020 | 30 |
About Wan-Jin Lu
Wan-Jin Lu is a scholar working on Molecular Biology, Genetics, Oncology, Aging and Radiology, Nuclear Medicine and Imaging, having authored 30 papers that have together received 4.1k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (10 papers), Cancer-related Molecular Pathways (5 papers), Hedgehog Signaling Pathway Studies (5 papers), Mesenchymal stem cell research (4 papers), Cell death mechanisms and regulation (3 papers), Bone Metabolism and Diseases (2 papers), Genetics, Aging, and Longevity in Model Organisms (2 papers) and Cancer, Hypoxia, and Metabolism (1 paper). The work is most often cited by research in Aging (455 citations), Genetics (485 citations), Molecular Biology (2.1k citations), Rheumatology (198 citations) and Physiology (363 citations). Wan-Jin Lu has collaborated with scholars based in United States, China and South Korea. Frequent co-authors include John Abrams, James F. Amatruda, Philip A. Beachy, Joseph A. Chapo, Ignasi Roig, Su Kit Chew, Antony Rodriguez, Sharad Kumar, Kathryn Mills and Fatih Akdemir. Their work appears in journals such as Nature, Science, Cell, Proceedings of the National Academy of Sciences and Nature Communications.
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.