Hui Shen
Impact in
- Cancer Research top 0.01%
- Cancer Genomics and Diagnostics
- Cancer-related molecular mechanisms research
- Oncology top 0.05%
- Cancer Immunotherapy and Biomarkers
Papers in
-
- Cancer Genomics and Diagnostics 58
- Cancer-related molecular mechanisms research 10
-
- Epigenetics and DNA Methylation 35
- RNA modifications and cancer 21
- Genomics and Chromatin Dynamics 14
- Co-authors
- Peter W. Laird (18 shared papers)Scott L. Carter (3 shared papers)Gad A. Getz (3 shared papers)Douglas A. Levine (2 shared papers)Gordon Brent Mills (1 shared paper)Kosuke Yoshihara (1 shared paper)Katherine Stemke‐Hale (1 shared paper)Rahulsimham Vegesna (1 shared paper)
- Journals
- Nature Communications (19 papers)Cell (13 papers)Cancer Cell (12 papers)Cell Reports (11 papers)Nature (10 papers)
- Partner nations
- United StatesChinaCanada
In The Last Decade
Hui Shen
208 papers receiving 62.0k citations
Hui Shen's Hit Papers
Peers
Comparison fields: 5 of 198
- Cancer Research 20.0k
- Oncology 14.2k
- Pulmonary and Respiratory Medicine 13.8k
- Molecular Biology 29.4k
- Genetics 3.5k
Countries citing papers authored by Hui Shen
This map shows the geographic impact of Hui Shen'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 Hui Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hui Shen more than expected).
Fields of papers citing papers by Hui Shen
This network shows the impact of papers produced by Hui Shen. 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 Hui Shen. The network helps show where Hui Shen may publish in the future.
Co-authors
The 25 scholars most cited alongside Hui Shen, 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 211 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Inferring tumour purity and stromal and immune cell admixture from expression data Hit paper breakdown → | 2013 | 6781 |
| 2 | Comprehensive molecular characterization of gastric adenocarcinoma Hit paper breakdown → | 2014 | 5209 |
| 3 | An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics Hit paper breakdown → | 2018 | 2602 |
| 4 | The Molecular Taxonomy of Primary Prostate Cancer Hit paper breakdown → | 2015 | 2435 |
| 5 | Comprehensive molecular characterization of urothelial bladder carcinoma Hit paper breakdown → | 2014 | 2419 |
| 6 | The repertoire of mutational signatures in human cancer Hit paper breakdown → | 2020 | 2339 |
| 7 | Pan-cancer analysis of whole genomes Hit paper breakdown → | 2020 | 2109 |
| 8 | Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma Hit paper breakdown → | 2017 | 1970 |
| 9 | Identification of a CpG Island Methylator Phenotype that Defines a Distinct Subgroup of Glioma Hit paper breakdown → | 2010 | 1943 |
| 10 | Comprehensive analyses of tumor immunity: implications for cancer immunotherapy Hit paper breakdown → | 2016 | 1731 |
| 11 | Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer Hit paper breakdown → | 2018 | 1720 |
| 12 | Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma Hit paper breakdown → | 2016 | 1643 |
| 13 | Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation Hit paper breakdown → | 2018 | 1617 |
| 14 | Absolute quantification of somatic DNA alterations in human cancer Hit paper breakdown → | 2012 | 1565 |
| 15 | Integrated Genomic Characterization of Pancreatic Ductal Adenocarcinoma Hit paper breakdown → | 2017 | 1559 |
| 16 | Comprehensive Molecular Portraits of Invasive Lobular Breast Cancer Hit paper breakdown → | 2015 | 1471 |
| 17 | Pan-cancer patterns of somatic copy number alteration Hit paper breakdown → | 2013 | 1424 |
| 18 | Multiplatform Analysis of 12 Cancer Types Reveals Molecular Classification within and across Tissues of Origin Hit paper breakdown → | 2014 | 1158 |
| 19 | The chromatin accessibility landscape of primary human cancers Hit paper breakdown → | 2018 | 802 |
| 20 | Genomic and Functional Approaches to Understanding Cancer Aneuploidy Hit paper breakdown → | 2018 | 749 |
About Hui Shen
Hui Shen is a scholar working on Cancer Research, Molecular Biology, Oncology, Pathology and Forensic Medicine and Pulmonary and Respiratory Medicine, having authored 211 papers that have together received 62.7k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (58 papers), Epigenetics and DNA Methylation (35 papers), RNA modifications and cancer (21 papers), Genetic factors in colorectal cancer (17 papers), Genomics and Chromatin Dynamics (14 papers), Pancreatic and Hepatic Oncology Research (11 papers), Ferroptosis and cancer prognosis (10 papers) and Cancer-related molecular mechanisms research (10 papers). The work is most often cited by research in Cancer Research (20.0k citations), Oncology (14.2k citations), Pulmonary and Respiratory Medicine (13.8k citations), Molecular Biology (29.4k citations) and Genetics (3.5k citations). Hui Shen has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Peter W. Laird, Scott L. Carter, Gad A. Getz, Douglas A. Levine, Gordon Brent Mills, Kosuke Yoshihara, Katherine Stemke‐Hale, Rahulsimham Vegesna, Wandaliz Torres‐García and Roel G.W. Verhaak. Their work appears in journals such as Nature Communications, Cell, Cancer Cell, Cell Reports 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.