Marc S. Greenblatt
- Cancer Research top 0.5%
- Cancer Genomics and Diagnostics 18
- Oncology top 0.5%
- Cancer-related Molecular Pathways 13
- Genetics top 0.5%
- Genomics and Rare Diseases 23
- BRCA gene mutations in cancer 11
- Genomic variations and chromosomal abnormalities 7
- Pathology and Forensic Medicine top 0.5%
- Genetic factors in colorectal cancer 22
- Biotechnology top 0.5%
-
- Genomics and Phylogenetic Studies 8
- DNA Repair Mechanisms 6
- Co-authors
- C C HarrisW P BennettMonica HollsteinSean V. TavtigianJohan T. den DunnenRaymond DalgleishDonna MaglottAnne‐Françoise Roux
- Cited by
- Cancer ResearchOncologyGenetics
- Partner nations
- United StatesAustraliaFrance
In The Last Decade
Marc S. Greenblatt
62 papers receiving 7.7k citations
Hit Papers
Peers
Comparison fields: 5 of 130
- Cancer Research 2.0k
- Oncology 3.3k
- Genetics 2.2k
- Pathology and Forensic Medicine 1.3k
- Biotechnology 595
Countries citing papers authored by Marc S. Greenblatt
This map shows the geographic impact of Marc S. Greenblatt'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 Marc S. Greenblatt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marc S. Greenblatt more than expected).
Fields of papers citing papers by Marc S. Greenblatt
This network shows the impact of papers produced by Marc S. Greenblatt. 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 Marc S. Greenblatt. The network helps show where Marc S. Greenblatt may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Marc S. Greenblatt, 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 | 2025 | 1 | |
| 2 | 2024 | 2 | |
| 3 | 2024 | 5 | |
| 4 | 2024 | 6 | |
| 5 | 2020 | 16 | |
| 6 | Modeling the ACMG/AMP variant classification guidelines as a Bayesian classification frameworkbreakdown → | 2018 | 279 |
| 7 | 2016 | 11 | |
| 8 | 2016 | 17 | |
| 9 | 2015 | 1 | |
| 10 | 2015 | 0 | |
| 11 | 2011 | 30 | |
| 12 | 2008 | 30 | |
| 13 | Sequence variant classification and reporting: recommendations for improving the interpretation of cancer susceptibility genetic test resultsbreakdown → | 2008 | 582 |
| 14 | 2008 | 60 | |
| 15 | 2008 | 125 | |
| 16 | 2008 | 7 | |
| 17 | 2007 | 9 | |
| 18 | 2006 | 54 | |
| 19 | 2004 | 1 | |
| 20 | 1999 | 16 |
About Marc S. Greenblatt
Marc S. Greenblatt is a scholar working on Cancer Research, Pathology and Forensic Medicine and Genetics, having authored 64 papers that have together received 7.8k indexed citations. Recurring topics across this work include Genomics and Rare Diseases (23 papers), Genetic factors in colorectal cancer (22 papers), Cancer Genomics and Diagnostics (18 papers), Cancer-related Molecular Pathways (13 papers), BRCA gene mutations in cancer (11 papers), Genomics and Phylogenetic Studies (8 papers), Genomic variations and chromosomal abnormalities (7 papers) and DNA Repair Mechanisms (6 papers). The work is most often cited by research in Cancer Research (2.0k citations), Oncology (3.3k citations) and Genetics (2.2k citations). Marc S. Greenblatt has collaborated with scholars based in United States, Australia and France. Frequent co-authors include C C Harris, W P Bennett, Monica Hollstein, Sean V. Tavtigian, Johan T. den Dunnen, Raymond Dalgleish, Donna Maglott, Anne‐Françoise Roux, Jean McGowan‐Jordan and Stylianos E. Antonarakis. Their work appears in journals such as Human Mutation, Genetics in Medicine, Familial Cancer, Cancer Investigation and Oncogene.
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.