Daniel M. Klass
Impact in
- Cancer Research top 2%
- Cancer Genomics and Diagnostics
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- Genetic factors in colorectal cancer
Papers in
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- Cancer Genomics and Diagnostics 13
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- RNA modifications and cancer 4
- RNA and protein synthesis mechanisms 3
- RNA Research and Splicing 3
- Co-authors
- Patrick O. Brown (3 shared papers)Maximilian Diehn (6 shared papers)Alexander F. Lovejoy (10 shared papers)David M. Kurtz (7 shared papers)Aaron M. Newman (6 shared papers)Florian Scherer (5 shared papers)Li Zhou (4 shared papers)Chih Long Liu (4 shared papers)
- Journals
- Journal of Clinical Oncology (5 papers)Blood (3 papers)PLoS ONE (3 papers)Nature Genetics (1 paper)Journal of Thoracic Oncology (1 paper)
- Partner nations
- United StatesSwitzerlandGermany
In The Last Decade
Daniel M. Klass
18 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 70
- Cancer Research 745
- Pathology and Forensic Medicine 223
- Oncology 328
- Pulmonary and Respiratory Medicine 380
- Molecular Biology 592
Countries citing papers authored by Daniel M. Klass
This map shows the geographic impact of Daniel M. Klass'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 Daniel M. Klass with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel M. Klass more than expected).
Fields of papers citing papers by Daniel M. Klass
This network shows the impact of papers produced by Daniel M. Klass. 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 Daniel M. Klass. The network helps show where Daniel M. Klass may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel M. Klass, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Integrated digital error suppression for improved detection of circulating tumor DNA Hit paper breakdown → | 2016 | 716 |
| 2 | 2006 | 133 | |
| 3 | 2010 | 133 | |
| 4 | 2013 | 49 | |
| 5 | 2019 | 40 | |
| 6 | 2015 | 28 | |
| 7 | 2013 | 17 | |
| 8 | 2022 | 17 | |
| 9 | 2016 | 10 | |
| 10 | 2015 | 9 | |
| 11 | 2022 | 8 | |
| 12 | 2015 | 7 | |
| 13 | 2019 | 4 | |
| 14 | 2016 | 4 | |
| 15 | 2013 | 2 | |
| 16 | 2019 | 1 | |
| 17 | 2019 | 1 | |
| 18 | 2016 | 1 | |
| 19 | 2018 | 0 |
About Daniel M. Klass
Daniel M. Klass is a scholar working on Cancer Research, Molecular Biology, Pathology and Forensic Medicine, Pulmonary and Respiratory Medicine and Oncology, having authored 19 papers that have together received 1.2k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (13 papers), Lung Cancer Treatments and Mutations (6 papers), Lymphoma Diagnosis and Treatment (4 papers), RNA modifications and cancer (4 papers), RNA and protein synthesis mechanisms (3 papers), RNA Research and Splicing (3 papers), Genetic factors in colorectal cancer (2 papers) and CAR-T cell therapy research (2 papers). The work is most often cited by research in Cancer Research (745 citations), Pathology and Forensic Medicine (223 citations), Oncology (328 citations), Pulmonary and Respiratory Medicine (380 citations) and Molecular Biology (592 citations). Daniel M. Klass has collaborated with scholars based in United States, Switzerland and Germany. Frequent co-authors include Patrick O. Brown, Maximilian Diehn, Alexander F. Lovejoy, David M. Kurtz, Aaron M. Newman, Florian Scherer, Li Zhou, Chih Long Liu, Jacob J. Chabon and Ash A. Alizadeh. Their work appears in journals such as Journal of Clinical Oncology, Blood, PLoS ONE, Nature Genetics and Journal of Thoracic Oncology.
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.