Xiaolin Bi
Impact in
- Aging top 5%
- Genetics, Aging, and Longevity in Model Organisms
- Epidemiology top 2%
- Autophagy in Disease and Therapy
Papers in
- Aging 5
- Genetics, Aging, and Longevity in Model Organisms 5
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- DNA Repair Mechanisms 4
- Developmental Biology and Gene Regulation 4
- Mitochondrial Function and Pathology 2
- Co-authors
- Yikang S. Rong (4 shared papers)Deepa Srikanta (3 shared papers)Ying Li (1 shared paper)Qingxi Yuan (1 shared paper)Huarui Zhu (1 shared paper)Qin Wang (1 shared paper)Quanyi Guo (1 shared paper)Xueyun Gao (1 shared paper)
- Journals
- Proceedings of the National Academy of Sciences (3 papers)Genetics (2 papers)Cancer Letters (2 papers)Oncogene (2 papers)Biomaterials (2 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Xiaolin Bi
38 papers receiving 3.3k citations
Xiaolin Bi's Hit Papers
Peers
Comparison fields: 5 of 124
- Aging 75
- Epidemiology 1.1k
- Cell Biology 226
- Molecular Biology 790
- Physiology 275
Countries citing papers authored by Xiaolin Bi
This map shows the geographic impact of Xiaolin Bi'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 Xiaolin Bi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaolin Bi more than expected).
Fields of papers citing papers by Xiaolin Bi
This network shows the impact of papers produced by Xiaolin Bi. 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 Xiaolin Bi. The network helps show where Xiaolin Bi may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaolin Bi, 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 40 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition) 1 Hit paper breakdown → | 2021 | 2067 |
| 2 | 2011 | 173 | |
| 3 | 2004 | 91 | |
| 4 | 2015 | 91 | |
| 5 | 2005 | 77 | |
| 6 | 2019 | 76 | |
| 7 | 2011 | 74 | |
| 8 | 2014 | 55 | |
| 9 | 2014 | 52 | |
| 10 | 2014 | 52 | |
| 11 | 2014 | 48 | |
| 12 | 2014 | 36 | |
| 13 | 2001 | 34 | |
| 14 | 2012 | 32 | |
| 15 | 2009 | 31 | |
| 16 | 2016 | 31 | |
| 17 | 2005 | 30 | |
| 18 | 2019 | 29 | |
| 19 | 2017 | 26 | |
| 20 | 2005 | 24 |
About Xiaolin Bi
Xiaolin Bi is a scholar working on Aging, Molecular Biology, Cancer Research, Cell Biology and Oncology, having authored 40 papers that have together received 3.3k indexed citations. Recurring topics across this work include Genetics, Aging, and Longevity in Model Organisms (5 papers), DNA Repair Mechanisms (4 papers), Cancer-related Molecular Pathways (4 papers), Autophagy in Disease and Therapy (4 papers), Developmental Biology and Gene Regulation (4 papers), Cancer-related molecular mechanisms research (3 papers), Telomeres, Telomerase, and Senescence (3 papers) and Mitochondrial Function and Pathology (2 papers). The work is most often cited by research in Aging (75 citations), Epidemiology (1.1k citations), Cell Biology (226 citations), Molecular Biology (790 citations) and Physiology (275 citations). Xiaolin Bi has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Yikang S. Rong, Deepa Srikanta, Ying Li, Qingxi Yuan, Huarui Zhu, Qin Wang, Quanyi Guo, Xueyun Gao, Zengqiang Yuan and Songshu Meng. Their work appears in journals such as Proceedings of the National Academy of Sciences, Genetics, Cancer Letters, Oncogene and Biomaterials.
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.