Da Li
Impact in
- Process Chemistry and Technology top 10%
- Molecular Biology top 10%
- RNA Interference and Gene Delivery
- Advanced biosensing and bioanalysis techniques
- CRISPR and Genetic Engineering
- Epigenetics and DNA Methylation
Papers in
-
- RNA Interference and Gene Delivery 10
- Advanced biosensing and bioanalysis techniques 7
- Chemical Synthesis and Analysis 4
- Oncology 16
- Cancer Immunotherapy and Biomarkers 4
- Co-authors
- Xiao‐Feng Wu (6 shared papers)Jin‐Bao Peng (6 shared papers)Hongming Pan (11 shared papers)Hui‐Qing Geng (4 shared papers)Fu‐Peng Wu (4 shared papers)Jun Ying (3 shared papers)Huhu Xin (2 shared papers)Hai Yu (5 shared papers)
- Journals
- Organic Letters (3 papers)Cancer Letters (2 papers)Therapeutic Advances in Medical Oncology (2 papers)Medical Oncology (2 papers)Oncotarget (2 papers)
- Partner nations
- ChinaGermanyUnited States
In The Last Decade
Da Li
80 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 129
- Process Chemistry and Technology 38
- Molecular Biology 741
- Business and International Management 19
- Cancer Research 145
- Organic Chemistry 269
Countries citing papers authored by Da Li
This map shows the geographic impact of Da 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 Da Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Da Li more than expected).
Fields of papers citing papers by Da Li
This network shows the impact of papers produced by Da 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 Da Li. The network helps show where Da Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Da 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
Showing the 20 most-cited of 82 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 109 | |
| 2 | 2018 | 93 | |
| 3 | 2016 | 89 | |
| 4 | 2006 | 67 | |
| 5 | 2011 | 66 | |
| 6 | 2018 | 63 | |
| 7 | 2014 | 55 | |
| 8 | 2019 | 53 | |
| 9 | 2015 | 48 | |
| 10 | 2019 | 45 | |
| 11 | 2010 | 45 | |
| 12 | 2019 | 37 | |
| 13 | 2013 | 31 | |
| 14 | 2021 | 31 | |
| 15 | 2016 | 30 | |
| 16 | 2015 | 30 | |
| 17 | 2007 | 29 | |
| 18 | 2020 | 29 | |
| 19 | 2007 | 26 | |
| 20 | 2018 | 26 |
About Da Li
Da Li is a scholar working on Molecular Biology, Oncology, Pulmonary and Respiratory Medicine, Organic Chemistry and Genetics, having authored 82 papers that have together received 1.5k indexed citations. Recurring topics across this work include RNA Interference and Gene Delivery (10 papers), Advanced biosensing and bioanalysis techniques (7 papers), Virus-based gene therapy research (6 papers), Hepatocellular Carcinoma Treatment and Prognosis (4 papers), Chemical Synthesis and Analysis (4 papers), Cancer Immunotherapy and Biomarkers (4 papers), Cancer Mechanisms and Therapy (4 papers) and Catalytic Cross-Coupling Reactions (4 papers). The work is most often cited by research in Process Chemistry and Technology (38 citations), Molecular Biology (741 citations), Business and International Management (19 citations), Cancer Research (145 citations) and Organic Chemistry (269 citations). Da Li has collaborated with scholars based in China, Germany and United States. Frequent co-authors include Xiao‐Feng Wu, Jin‐Bao Peng, Hongming Pan, Hui‐Qing Geng, Fu‐Peng Wu, Jun Ying, Huhu Xin, Hai Yu, Guping Tang and Hongliang Huang. Their work appears in journals such as Organic Letters, Cancer Letters, Therapeutic Advances in Medical Oncology, Medical Oncology and Oncotarget.
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.