Daniel A. Ritt
Impact in
- Molecular Biology top 5%
- Melanoma and MAPK Pathways
- Protein Kinase Regulation and GTPase Signaling
- PI3K/AKT/mTOR signaling in cancer
- Protein Tyrosine Phosphatases
- Ubiquitin and proteasome pathways
- Cell Biology top 5%
Papers in
-
- Melanoma and MAPK Pathways 14
- Protein Kinase Regulation and GTPase Signaling 12
- Signaling Pathways in Disease 5
- Protein Tyrosine Phosphatases 3
- DNA Repair Mechanisms 2
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- Cellular Mechanics and Interactions 3
- Co-authors
- Deborah K. Morrison (25 shared papers)Ming Zhou (7 shared papers)Timothy D. Veenstra (4 shared papers)Alyson K. Freeman (2 shared papers)Terry D. Copeland (3 shared papers)Suzanne I. Specht (5 shared papers)Jürgen Müller (2 shared papers)Thomas P. Conrads (2 shared papers)
- Journals
- Molecular Cell (6 papers)Current Biology (3 papers)Proceedings of the National Academy of Sciences (3 papers)Cancer Discovery (2 papers)Developmental Cell (1 paper)
- Partner nations
- United StatesFranceDenmark
In The Last Decade
Daniel A. Ritt
25 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 91
- Molecular Biology 1.5k
- Cell Biology 270
- Oncology 375
- Pathology and Forensic Medicine 226
- Computational Theory and Mathematics 166
Countries citing papers authored by Daniel A. Ritt
This map shows the geographic impact of Daniel A. Ritt'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 A. Ritt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel A. Ritt more than expected).
Fields of papers citing papers by Daniel A. Ritt
This network shows the impact of papers produced by Daniel A. Ritt. 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 A. Ritt. The network helps show where Daniel A. Ritt may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel A. Ritt, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2005 | 477 | |
| 2 | 2009 | 178 | |
| 3 | 2013 | 160 | |
| 4 | 2009 | 118 | |
| 5 | 2009 | 93 | |
| 6 | 2006 | 79 | |
| 7 | 2016 | 78 | |
| 8 | 2013 | 75 | |
| 9 | 2019 | 66 | |
| 10 | 2011 | 65 | |
| 11 | 2003 | 61 | |
| 12 | 2015 | 53 | |
| 13 | 2014 | 51 | |
| 14 | 2019 | 47 | |
| 15 | 2021 | 43 | |
| 16 | 2010 | 38 | |
| 17 | 2016 | 30 | |
| 18 | 2012 | 29 | |
| 19 | 2019 | 23 | |
| 20 | 2022 | 16 |
About Daniel A. Ritt
Daniel A. Ritt is a scholar working on Molecular Biology, Cell Biology, Pathology and Forensic Medicine, Computational Theory and Mathematics and Genetics, having authored 26 papers that have together received 1.8k indexed citations. Recurring topics across this work include Melanoma and MAPK Pathways (14 papers), Protein Kinase Regulation and GTPase Signaling (12 papers), Signaling Pathways in Disease (5 papers), Cellular Mechanics and Interactions (3 papers), Protein Tyrosine Phosphatases (3 papers), DNA Repair Mechanisms (2 papers), Computational Drug Discovery Methods (2 papers) and Cancer Mechanisms and Therapy (2 papers). The work is most often cited by research in Molecular Biology (1.5k citations), Cell Biology (270 citations), Oncology (375 citations), Pathology and Forensic Medicine (226 citations) and Computational Theory and Mathematics (166 citations). Daniel A. Ritt has collaborated with scholars based in United States, France and Denmark. Frequent co-authors include Deborah K. Morrison, Ming Zhou, Timothy D. Veenstra, Alyson K. Freeman, Terry D. Copeland, Suzanne I. Specht, Jürgen Müller, Thomas P. Conrads, Melissa McKay and M. K. Dougherty. Their work appears in journals such as Molecular Cell, Current Biology, Proceedings of the National Academy of Sciences, Cancer Discovery and Developmental Cell.
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.