Jun Li
Impact in
- Cancer Research top 0.05%
- Cancer Genomics and Diagnostics
- Cancer-related molecular mechanisms research
- Genetics top 0.05%
- Glioma Diagnosis and Treatment
Papers in
-
- Cancer Genomics and Diagnostics 40
- Cancer-related molecular mechanisms research 25
- MicroRNA in disease regulation 12
-
- Bioinformatics and Genomic Networks 16
- Epigenetics and DNA Methylation 15
- Advanced Biosensing Techniques and Applications 9
- Co-authors
- Han Liang (18 shared papers)Leng Han (3 shared papers)John N. Weinstein (3 shared papers)Gordon Brent Mills (11 shared papers)Paul L. Roebuck (3 shared papers)Lingxiang Liu (2 shared papers)Yuan Yuan (2 shared papers)Lixia Diao (2 shared papers)
- Journals
- Nature Communications (17 papers)Cancer Cell (9 papers)Cell (9 papers)Frontiers in Oncology (6 papers)Cell Reports (6 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Jun Li
241 papers receiving 38.9k citations
Jun Li's Hit Papers
Peers
Comparison fields: 5 of 169
- Cancer Research 10.6k
- Genetics 6.6k
- Oncology 5.9k
- Molecular Biology 12.3k
- Pulmonary and Respiratory Medicine 3.2k
Countries citing papers authored by Jun Li
This map shows the geographic impact of Jun 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 Jun Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Li more than expected).
Fields of papers citing papers by Jun Li
This network shows the impact of papers produced by Jun 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 Jun Li. The network helps show where Jun Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun 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 254 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Comprehensive genomic characterization defines human glioblastoma genes and core pathways Hit paper breakdown → | 2008 | 6425 |
| 2 | The Somatic Genomic Landscape of Glioblastoma Hit paper breakdown → | 2013 | 4012 |
| 3 | The repertoire of mutational signatures in human cancer Hit paper breakdown → | 2020 | 2401 |
| 4 | Oncogenic Signaling Pathways in The Cancer Genome Atlas Hit paper breakdown → | 2018 | 2371 |
| 5 | Pan-cancer analysis of whole genomes Hit paper breakdown → | 2020 | 2169 |
| 6 | Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer Hit paper breakdown → | 2018 | 1758 |
| 7 | Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation Hit paper breakdown → | 2018 | 1634 |
| 8 | Multiplatform Analysis of 12 Cancer Types Reveals Molecular Classification within and across Tissues of Origin Hit paper breakdown → | 2014 | 1167 |
| 9 | Genomic and Functional Approaches to Understanding Cancer Aneuploidy Hit paper breakdown → | 2018 | 768 |
| 10 | Comprehensive Analysis of Alternative Splicing Across Tumors from 8,705 Patients Hit paper breakdown → | 2018 | 696 |
| 11 | Pathogenic Germline Variants in 10,389 Adult Cancers Hit paper breakdown → | 2018 | 617 |
| 12 | Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines Hit paper breakdown → | 2018 | 598 |
| 13 | The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma Hit paper breakdown → | 2018 | 580 |
| 14 | Patterns of somatic structural variation in human cancer genomes Hit paper breakdown → | 2020 | 564 |
| 15 | Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing Hit paper breakdown → | 2020 | 489 |
| 16 | A pan-cancer proteomic perspective on The Cancer Genome Atlas Hit paper breakdown → | 2014 | 468 |
| 17 | Driver Fusions and Their Implications in the Development and Treatment of Human Cancers Hit paper breakdown → | 2018 | 457 |
| 18 | The Immune Landscape of Cancer Hit paper breakdown → | 2019 | 455 |
| 19 | 2015 | 439 | |
| 20 | 2015 | 417 |
About Jun Li
Jun Li is a scholar working on Cancer Research, Molecular Biology, Pathology and Forensic Medicine, Spectroscopy and Oncology, having authored 254 papers that have together received 39.4k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (40 papers), Cancer-related molecular mechanisms research (25 papers), Advanced Proteomics Techniques and Applications (21 papers), Bioinformatics and Genomic Networks (16 papers), Epigenetics and DNA Methylation (15 papers), Lymphoma Diagnosis and Treatment (14 papers), MicroRNA in disease regulation (12 papers) and Advanced Biosensing Techniques and Applications (9 papers). The work is most often cited by research in Cancer Research (10.6k citations), Genetics (6.6k citations), Oncology (5.9k citations), Molecular Biology (12.3k citations) and Pulmonary and Respiratory Medicine (3.2k citations). Jun Li has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Han Liang, Leng Han, John N. Weinstein, Gordon Brent Mills, Paul L. Roebuck, Lingxiang Liu, Yuan Yuan, Lixia Diao, Rehan Akbani and Cyriac Kandoth. Their work appears in journals such as Nature Communications, Cancer Cell, Cell, Frontiers in Oncology and Cell 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.