David M. Livingston
- Oncology top 0.02%
- Cancer-related Molecular Pathways 62
- Polyomavirus and related diseases 29
- Cancer Research top 0.05%
- Molecular Biology top 0.02%
- DNA Repair Mechanisms 54
- CRISPR and Genetic Engineering 35
- Ubiquitin and proteasome pathways 24
- Genetics top 0.02%
- Virus-based gene therapy research 60
- BRCA gene mutations in cancer 32
- Cell Biology top 0.2%
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- Bacteriophages and microbial interactions 22
- Co-authors
- Ralph ScullyJames A. DeCaprioRichard EcknerWilliam G. KaelinAndrew L. KungZoltàn AranyMark E. EwenJohn W. Ludlow
- Partner nations
- United StatesFranceUnited Kingdom
In The Last Decade
David M. Livingston
250 papers receiving 40.1k citations
Hit Papers
Peers
Comparison fields: 5 of 161
- Oncology 16.1k
- Cancer Research 7.6k
- Molecular Biology 30.8k
- Genetics 10.6k
- Cell Biology 3.0k
Countries citing papers authored by David M. Livingston
This map shows the geographic impact of David M. Livingston'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 David M. Livingston with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David M. Livingston more than expected).
Fields of papers citing papers by David M. Livingston
This network shows the impact of papers produced by David M. Livingston. 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 David M. Livingston. The network helps show where David M. Livingston may publish in the future.
Co-authorship network
The 25 scholars most cited alongside David M. Livingston, 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 | 2019 | 67 | |
| 2 | 2014 | 136 | |
| 3 | 2014 | 53 | |
| 4 | 2011 | 88 | |
| 5 | 2011 | 189 | |
| 6 | 2010 | 87 | |
| 7 | 2010 | 211 | |
| 8 | RAP80 Targets BRCA1 to Specific Ubiquitin Structures at DNA Damage Sitesbreakdown → | 2007 | 553 |
| 9 | Dicer-deficient mouse embryonic stem cells are defective in differentiation and centromeric silencingbreakdown → | 2005 | 995 |
| 10 | 2004 | 193 | |
| 11 | A Complex with Chromatin Modifiers That Occupies E2F- and Myc-Responsive Genes in G 0 Cellsbreakdown → | 2002 | 610 |
| 12 | 2002 | 20 | |
| 13 | 2001 | 94 | |
| 14 | 2000 | 229 | |
| 15 | Suppression of tumor growth through disruption of hypoxia-inducible transcriptionbreakdown → | 2000 | 436 |
| 16 | 1998 | 364 | |
| 17 | 1993 | 88 | |
| 18 | Growth inhibition by TGF-β linked to suppression of retinoblastoma protein phosphorylationbreakdown → | 1990 | 710 |
| 19 | 1973 | 78 | |
| 20 | 1971 | 13 |
About David M. Livingston
David M. Livingston is a scholar working on Oncology, Genetics and Molecular Biology, having authored 251 papers that have together received 41.4k indexed citations. Recurring topics across this work include Cancer-related Molecular Pathways (62 papers), Virus-based gene therapy research (60 papers), DNA Repair Mechanisms (54 papers), CRISPR and Genetic Engineering (35 papers), BRCA gene mutations in cancer (32 papers), Polyomavirus and related diseases (29 papers), Ubiquitin and proteasome pathways (24 papers) and Bacteriophages and microbial interactions (22 papers). The work is most often cited by research in Oncology (16.1k citations), Cancer Research (7.6k citations) and Molecular Biology (30.8k citations). David M. Livingston has collaborated with scholars based in United States, France and United Kingdom. Frequent co-authors include Ralph Scully, James A. DeCaprio, Richard Eckner, William G. Kaelin, Andrew L. Kung, Zoltàn Arany, Mark E. Ewen, John W. Ludlow, Shridar Ganesan and Eric Huang.
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.