Xi Long
Impact in
- Aging top 5%
- Genetics, Aging, and Longevity in Model Organisms
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- Neurobiology and Insect Physiology Research
Papers in
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- Neurobiology and Insect Physiology Research 10
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- DNA and Nucleic Acid Chemistry 5
- Advanced biosensing and bioanalysis techniques 4
- RNA Interference and Gene Delivery 4
- Co-authors
- Michael D. Stone (5 shared papers)Robert H. Singer (6 shared papers)Joseph W. Parks (4 shared papers)Clive R. Bagshaw (2 shared papers)Matthias Schlichting (2 shared papers)Allan M. Wong (4 shared papers)Katharine C. Abruzzi (2 shared papers)Michael Rosbash (2 shared papers)
- Journals
- eLife (4 papers)Nature Methods (2 papers)Current Biology (2 papers)Methods (1 paper)Neural Development (1 paper)
- Partner nations
- United StatesGermanyCanada
In The Last Decade
Xi Long
18 papers receiving 743 citations
Peers
Comparison fields: 5 of 75
- Aging 51
- Cellular and Molecular Neuroscience 402
- Endocrine and Autonomic Systems 119
- Structural Biology 12
- Biophysics 38
Countries citing papers authored by Xi Long
This map shows the geographic impact of Xi Long'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 Xi Long with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xi Long more than expected).
Fields of papers citing papers by Xi Long
This network shows the impact of papers produced by Xi Long. 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 Xi Long. The network helps show where Xi Long may publish in the future.
Co-authors
The 25 scholars most cited alongside Xi Long, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 94 | |
| 2 | 2019 | 83 | |
| 3 | 2021 | 79 | |
| 4 | 2019 | 64 | |
| 5 | 2017 | 62 | |
| 6 | 2019 | 58 | |
| 7 | 2018 | 53 | |
| 8 | 2013 | 47 | |
| 9 | 2019 | 44 | |
| 10 | 2022 | 41 | |
| 11 | 2019 | 27 | |
| 12 | 2022 | 25 | |
| 13 | 2014 | 22 | |
| 14 | 2016 | 21 | |
| 15 | 2018 | 20 | |
| 16 | 2014 | 2 | |
| 17 | 2022 | 2 | |
| 18 | 2017 | 1 |
About Xi Long
Xi Long is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology, Ecology, Genetics and Endocrine and Autonomic Systems, having authored 18 papers that have together received 745 indexed citations. Recurring topics across this work include Neurobiology and Insect Physiology Research (10 papers), DNA and Nucleic Acid Chemistry (5 papers), Advanced biosensing and bioanalysis techniques (4 papers), Insect and Arachnid Ecology and Behavior (4 papers), Physiological and biochemical adaptations (4 papers), RNA Interference and Gene Delivery (4 papers), Circadian rhythm and melatonin (3 papers) and Animal Behavior and Reproduction (2 papers). The work is most often cited by research in Aging (51 citations), Cellular and Molecular Neuroscience (402 citations), Endocrine and Autonomic Systems (119 citations), Structural Biology (12 citations) and Biophysics (38 citations). Xi Long has collaborated with scholars based in United States, Germany and Canada. Frequent co-authors include Michael D. Stone, Robert H. Singer, Joseph W. Parks, Clive R. Bagshaw, Matthias Schlichting, Allan M. Wong, Katharine C. Abruzzi, Michael Rosbash, Timothée Lionnet and Tzumin Lee. Their work appears in journals such as eLife, Nature Methods, Current Biology, Methods and Neural Development.
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.