Tom Bodenheimer
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 46
- Cancer-related molecular mechanisms research 7
- Oncology 21
- Cancer-related Molecular Pathways 7
- Co-authors
- David T. Huang (1 shared paper)Courtney Rees Lyles (1 shared paper)Urmimala Sarkar (1 shared paper)Adam B. Schickedanz (1 shared paper)Andrea M. Lopez (1 shared paper)Steven Ross Brown (1 shared paper)
- Journals
- Cell (15 papers)Cell Reports (14 papers)Cancer Cell (13 papers)Nature (12 papers)Nature Communications (11 papers)
- Partner nations
- United StatesCanadaGermany
In The Last Decade
Tom Bodenheimer
84 papers receiving 66.3k citations
Tom Bodenheimer's Hit Papers
Peers
Comparison fields: 5 of 187
- Cancer Research 21.2k
- Oncology 16.7k
- Pulmonary and Respiratory Medicine 14.6k
- Molecular Biology 31.6k
- Pathology and Forensic Medicine 4.5k
Countries citing papers authored by Tom Bodenheimer
This map shows the geographic impact of Tom Bodenheimer'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 Tom Bodenheimer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom Bodenheimer more than expected).
Fields of papers citing papers by Tom Bodenheimer
This network shows the impact of papers produced by Tom Bodenheimer. 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 Tom Bodenheimer. The network helps show where Tom Bodenheimer may publish in the future.
Co-authors
The 6 scholars most cited alongside Tom Bodenheimer, 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 84 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Comprehensive molecular profiling of lung adenocarcinoma Hit paper breakdown → | 2014 | 4550 |
| 2 | The Immune Landscape of Cancer Hit paper breakdown → | 2018 | 4331 |
| 3 | Comprehensive genomic characterization of squamous cell lung cancers Hit paper breakdown → | 2012 | 3290 |
| 4 | Comprehensive molecular characterization of clear cell renal cell carcinoma Hit paper breakdown → | 2013 | 2829 |
| 5 | An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics Hit paper breakdown → | 2018 | 2602 |
| 6 | Genomic Classification of Cutaneous Melanoma Hit paper breakdown → | 2015 | 2509 |
| 7 | Integrated Genomic Characterization of Papillary Thyroid Carcinoma Hit paper breakdown → | 2014 | 2442 |
| 8 | The Molecular Taxonomy of Primary Prostate Cancer Hit paper breakdown → | 2015 | 2435 |
| 9 | Comprehensive molecular characterization of urothelial bladder carcinoma Hit paper breakdown → | 2014 | 2419 |
| 10 | The repertoire of mutational signatures in human cancer Hit paper breakdown → | 2020 | 2339 |
| 11 | Oncogenic Signaling Pathways in The Cancer Genome Atlas Hit paper breakdown → | 2018 | 2334 |
| 12 | Pan-cancer analysis of whole genomes Hit paper breakdown → | 2020 | 2109 |
| 13 | Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma Hit paper breakdown → | 2017 | 1970 |
| 14 | Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer Hit paper breakdown → | 2018 | 1720 |
| 15 | Comprehensive Characterization of Cancer Driver Genes and Mutations Hit paper breakdown → | 2018 | 1714 |
| 16 | Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma Hit paper breakdown → | 2016 | 1643 |
| 17 | Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation Hit paper breakdown → | 2018 | 1617 |
| 18 | Integrated Genomic Characterization of Pancreatic Ductal Adenocarcinoma Hit paper breakdown → | 2017 | 1559 |
| 19 | Comprehensive Molecular Portraits of Invasive Lobular Breast Cancer Hit paper breakdown → | 2015 | 1471 |
| 20 | Integrated genomic and molecular characterization of cervical cancer Hit paper breakdown → | 2017 | 1221 |
About Tom Bodenheimer
Tom Bodenheimer is a scholar working on Cancer Research, Oncology, Pathology and Forensic Medicine, Molecular Biology and Pulmonary and Respiratory Medicine, having authored 84 papers that have together received 67.1k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (46 papers), Genetic factors in colorectal cancer (14 papers), RNA modifications and cancer (13 papers), RNA Research and Splicing (8 papers), Cancer-related Molecular Pathways (7 papers), Cancer-related molecular mechanisms research (7 papers), Lung Cancer Treatments and Mutations (7 papers) and Genomics and Chromatin Dynamics (6 papers). The work is most often cited by research in Cancer Research (21.2k citations), Oncology (16.7k citations), Pulmonary and Respiratory Medicine (14.6k citations), Molecular Biology (31.6k citations) and Pathology and Forensic Medicine (4.5k citations). Tom Bodenheimer has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include David T. Huang, Courtney Rees Lyles, Urmimala Sarkar, Adam B. Schickedanz, Andrea M. Lopez and Steven Ross Brown. Their work appears in journals such as Cell, Cell Reports, Cancer Cell, Nature and Nature Communications.
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.