Long-Cheng Li
Impact in
- Cancer Research top 2%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Molecular Biology top 2%
- Epigenetics and DNA Methylation
- Cancer-related gene regulation
- RNA modifications and cancer
- RNA Research and Splicing
- RNA Interference and Gene Delivery
Papers in
-
- RNA Interference and Gene Delivery 5
- Cancer-related gene regulation 4
- RNA modifications and cancer 3
- Epigenetics and DNA Methylation 3
- RNA Research and Splicing 3
- CRISPR and Genetic Engineering 2
-
- MicroRNA in disease regulation 5
- Co-authors
- Rajvir Dahiya (4 shared papers)Vera Huang (7 shared papers)Robert F. Place (6 shared papers)Ji Wang (4 shared papers)Jingwei Yu (2 shared papers)Zhongxia Qi (2 shared papers)Ji Wang (2 shared papers)Victoria Portnoy (2 shared papers)
- Journals
- Nucleic Acids Research (2 papers)Cancer (1 paper)PLoS ONE (1 paper)Clinical Cancer Research (1 paper)PLoS Genetics (1 paper)
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Long-Cheng Li
14 papers receiving 3.2k citations
Long-Cheng Li's Hit Papers
Peers
Comparison fields: 5 of 115
- Cancer Research 800
- Molecular Biology 2.6k
- Genetics 480
- Oncology 270
- Immunology 201
Countries citing papers authored by Long-Cheng Li
This map shows the geographic impact of Long-Cheng 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 Long-Cheng Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Long-Cheng Li more than expected).
Fields of papers citing papers by Long-Cheng Li
This network shows the impact of papers produced by Long-Cheng 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 Long-Cheng Li. The network helps show where Long-Cheng Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Long-Cheng Li, 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 | MethPrimer: designing primers for methylation PCRs Hit paper breakdown → | 2002 | 2167 |
| 2 | 2011 | 236 | |
| 3 | 2006 | 163 | |
| 4 | 2010 | 145 | |
| 5 | 2010 | 118 | |
| 6 | 2013 | 103 | |
| 7 | 2001 | 66 | |
| 8 | 1999 | 49 | |
| 9 | 2003 | 46 | |
| 10 | 2012 | 41 | |
| 11 | 2012 | 35 | |
| 12 | 2015 | 29 | |
| 13 | 2014 | 14 | |
| 14 | 2012 | 11 |
About Long-Cheng Li
Long-Cheng Li is a scholar working on Molecular Biology, Cancer Research, Pulmonary and Respiratory Medicine, Genetics and Pathology and Forensic Medicine, having authored 14 papers that have together received 3.2k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (5 papers), RNA Interference and Gene Delivery (5 papers), Cancer-related gene regulation (4 papers), Prostate Cancer Treatment and Research (3 papers), RNA modifications and cancer (3 papers), Epigenetics and DNA Methylation (3 papers), RNA Research and Splicing (3 papers) and CRISPR and Genetic Engineering (2 papers). The work is most often cited by research in Cancer Research (800 citations), Molecular Biology (2.6k citations), Genetics (480 citations), Oncology (270 citations) and Immunology (201 citations). Long-Cheng Li has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Rajvir Dahiya, Vera Huang, Robert F. Place, Ji Wang, Jingwei Yu, Zhongxia Qi, Ji Wang, Victoria Portnoy, Xiaoling Wang and Marc Shuman. Their work appears in journals such as Nucleic Acids Research, Cancer, PLoS ONE, Clinical Cancer Research and PLoS Genetics.
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.