Yiling Lu
Impact in
- Cancer Research top 0.01%
- Cancer Genomics and Diagnostics
- Cancer-related molecular mechanisms research
- Oncology top 0.02%
- Cancer Immunotherapy and Biomarkers
Papers in
-
- Cancer Genomics and Diagnostics 60
-
- PI3K/AKT/mTOR signaling in cancer 44
- Advanced Biosensing Techniques and Applications 26
- RNA modifications and cancer 23
- RNA Research and Splicing 19
- Co-authors
- Gordon Brent Mills (145 shared papers)Bryan T. Hennessy (19 shared papers)Prahlad T. Ram (7 shared papers)Debra L. Smith (4 shared papers)Xianjun Fang (16 shared papers)Robert C. Bast (11 shared papers)Shuangxing Yu (20 shared papers)James Robert Woodgett (2 shared papers)
- Journals
- Cancer Cell (29 papers)Cell Reports (22 papers)Nature Communications (21 papers)Cell (18 papers)Nature (14 papers)
- Partner nations
- United StatesChinaCanada
In The Last Decade
Yiling Lu
321 papers receiving 98.4k citations
Yiling Lu's Hit Papers
Peers
Comparison fields: 5 of 200
- Cancer Research 28.0k
- Oncology 23.9k
- Molecular Biology 50.8k
- Pulmonary and Respiratory Medicine 17.7k
- Genetics 5.4k
Countries citing papers authored by Yiling Lu
This map shows the geographic impact of Yiling Lu'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 Yiling Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yiling Lu more than expected).
Fields of papers citing papers by Yiling Lu
This network shows the impact of papers produced by Yiling Lu. 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 Yiling Lu. The network helps show where Yiling Lu may publish in the future.
Co-authors
The 25 scholars most cited alongside Yiling Lu, 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 330 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Comprehensive molecular characterization of gastric adenocarcinoma Hit paper breakdown → | 2014 | 5209 |
| 2 | Comprehensive molecular profiling of lung adenocarcinoma Hit paper breakdown → | 2014 | 4550 |
| 3 | The Immune Landscape of Cancer Hit paper breakdown → | 2018 | 4331 |
| 4 | The Somatic Genomic Landscape of Glioblastoma Hit paper breakdown → | 2013 | 3977 |
| 5 | Comprehensive molecular characterization of clear cell renal cell carcinoma Hit paper breakdown → | 2013 | 2829 |
| 6 | An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics Hit paper breakdown → | 2018 | 2602 |
| 7 | Genomic Classification of Cutaneous Melanoma Hit paper breakdown → | 2015 | 2509 |
| 8 | Integrated Genomic Characterization of Papillary Thyroid Carcinoma Hit paper breakdown → | 2014 | 2442 |
| 9 | The Molecular Taxonomy of Primary Prostate Cancer Hit paper breakdown → | 2015 | 2435 |
| 10 | Exosomal PD-L1 contributes to immunosuppression and is associated with anti-PD-1 response Hit paper breakdown → | 2018 | 2378 |
| 11 | The repertoire of mutational signatures in human cancer Hit paper breakdown → | 2020 | 2339 |
| 12 | Oncogenic Signaling Pathways in The Cancer Genome Atlas Hit paper breakdown → | 2018 | 2334 |
| 13 | Next-generation characterization of the Cancer Cell Line Encyclopedia Hit paper breakdown → | 2019 | 2326 |
| 14 | Pan-cancer analysis of whole genomes Hit paper breakdown → | 2020 | 2109 |
| 15 | Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma Hit paper breakdown → | 2017 | 1970 |
| 16 | Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer Hit paper breakdown → | 2017 | 1931 |
| 17 | Exploiting the PI3K/AKT Pathway for Cancer Drug Discovery Hit paper breakdown → | 2005 | 1862 |
| 18 | Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer Hit paper breakdown → | 2018 | 1720 |
| 19 | Comprehensive Characterization of Cancer Driver Genes and Mutations Hit paper breakdown → | 2018 | 1714 |
| 20 | Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma Hit paper breakdown → | 2016 | 1643 |
About Yiling Lu
Yiling Lu is a scholar working on Cancer Research, Molecular Biology, Oncology, Pathology and Forensic Medicine and Cell Biology, having authored 330 papers that have together received 99.6k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (60 papers), PI3K/AKT/mTOR signaling in cancer (44 papers), Advanced Biosensing Techniques and Applications (26 papers), RNA modifications and cancer (23 papers), RNA Research and Splicing (19 papers), Genetic factors in colorectal cancer (18 papers), Advanced Proteomics Techniques and Applications (17 papers) and Cancer-related Molecular Pathways (15 papers). The work is most often cited by research in Cancer Research (28.0k citations), Oncology (23.9k citations), Molecular Biology (50.8k citations), Pulmonary and Respiratory Medicine (17.7k citations) and Genetics (5.4k citations). Yiling Lu has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Gordon Brent Mills, Bryan T. Hennessy, Prahlad T. Ram, Debra L. Smith, Xianjun Fang, Robert C. Bast, Shuangxing Yu, James Robert Woodgett, Ruth LaPushin and Zhenlin Ju. Their work appears in journals such as Cancer Cell, Cell Reports, Nature Communications, Cell and Nature.
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.