Nan Hao
Impact in
- Aging top 1%
- Genetics, Aging, and Longevity in Model Organisms
- Biophysics top 2%
Papers in
-
- Gene Regulatory Network Analysis 23
- Fungal and yeast genetics research 21
- Bioinformatics and Genomic Networks 7
- Single-cell and spatial transcriptomics 6
- CRISPR and Genetic Engineering 5
- RNA Research and Splicing 4
- DNA Repair Mechanisms 3
- Aging 11
- Genetics, Aging, and Longevity in Model Organisms 11
- Co-authors
- Erin K. O’Shea (3 shared papers)Henrik Dohlman (15 shared papers)Timothy C. Elston (14 shared papers)Marcelo Behar (5 shared papers)Lev S. Tsimring (11 shared papers)Jeff Hasty (12 shared papers)Yang Li (8 shared papers)Lorraine Pillus (7 shared papers)
- Journals
- Journal of Biological Chemistry (5 papers)Science (3 papers)eLife (3 papers)PLoS Computational Biology (3 papers)Scientific Reports (2 papers)
- Partner nations
- United StatesChinaRussia
In The Last Decade
Nan Hao
47 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 115
- Aging 189
- Biophysics 124
- Molecular Biology 1.3k
- Cell Biology 154
- Endocrine and Autonomic Systems 40
Countries citing papers authored by Nan Hao
This map shows the geographic impact of Nan Hao'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 Nan Hao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nan Hao more than expected).
Fields of papers citing papers by Nan Hao
This network shows the impact of papers produced by Nan Hao. 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 Nan Hao. The network helps show where Nan Hao may publish in the future.
Co-authors
The 25 scholars most cited alongside Nan Hao, 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 52 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 227 | |
| 2 | 2013 | 112 | |
| 3 | 2022 | 107 | |
| 4 | 2008 | 102 | |
| 5 | 2007 | 90 | |
| 6 | 2007 | 87 | |
| 7 | 2020 | 81 | |
| 8 | 2015 | 75 | |
| 9 | 2003 | 66 | |
| 10 | 2005 | 65 | |
| 11 | 2017 | 59 | |
| 12 | 2008 | 57 | |
| 13 | 2006 | 51 | |
| 14 | 2008 | 45 | |
| 15 | 2019 | 39 | |
| 16 | 2023 | 38 | |
| 17 | 2007 | 31 | |
| 18 | 2016 | 27 | |
| 19 | 2024 | 19 | |
| 20 | 2017 | 19 |
About Nan Hao
Nan Hao is a scholar working on Molecular Biology, Aging, Plant Science, Biomedical Engineering and Genetics, having authored 52 papers that have together received 1.6k indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (23 papers), Fungal and yeast genetics research (21 papers), Genetics, Aging, and Longevity in Model Organisms (11 papers), Bioinformatics and Genomic Networks (7 papers), Single-cell and spatial transcriptomics (6 papers), CRISPR and Genetic Engineering (5 papers), RNA Research and Splicing (4 papers) and DNA Repair Mechanisms (3 papers). The work is most often cited by research in Aging (189 citations), Biophysics (124 citations), Molecular Biology (1.3k citations), Cell Biology (154 citations) and Endocrine and Autonomic Systems (40 citations). Nan Hao has collaborated with scholars based in United States, China and Russia. Frequent co-authors include Erin K. O’Shea, Henrik Dohlman, Timothy C. Elston, Marcelo Behar, Lev S. Tsimring, Jeff Hasty, Yang Li, Lorraine Pillus, Jeremy Gunawardena and Bogdan Budnik. Their work appears in journals such as Journal of Biological Chemistry, Science, eLife, PLoS Computational Biology and Scientific Reports.
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.