Dáša Longman
Impact in
- Aging top 5%
- Genetics, Aging, and Longevity in Model Organisms
- Molecular Biology top 10%
- RNA Research and Splicing
- RNA and protein synthesis mechanisms
- RNA modifications and cancer
- RNA regulation and disease
- CRISPR and Genetic Engineering
- Genomics and Chromatin Dynamics
- Nuclear Structure and Function
Papers in
-
- RNA Research and Splicing 15
- RNA and protein synthesis mechanisms 7
- RNA modifications and cancer 5
- CRISPR and Genetic Engineering 5
- RNA regulation and disease 4
- Aging 5
- Genetics, Aging, and Longevity in Model Organisms 5
- Co-authors
- Javier F. Cáceres (16 shared papers)Nele Hug (5 shared papers)Iain L. Johnstone (5 shared papers)Ronald H.A. Plasterk (1 shared paper)Corina Anastasaki (2 shared papers)E. Elizabeth Patton (2 shared papers)Jeremy R. Sanford (1 shared paper)Susan McCracken (4 shared papers)
- Journals
- Nucleic Acids Research (3 papers)Genes & Development (2 papers)The EMBO Journal (2 papers)Journal of Biological Chemistry (2 papers)RNA (2 papers)
- Partner nations
- United KingdomCanadaGermany
In The Last Decade
Dáša Longman
18 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 78
- Aging 75
- Molecular Biology 1.1k
- Genetics 158
- Cancer Research 82
- Cell Biology 72
Countries citing papers authored by Dáša Longman
This map shows the geographic impact of Dáša Longman'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 Dáša Longman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dáša Longman more than expected).
Fields of papers citing papers by Dáša Longman
This network shows the impact of papers produced by Dáša Longman. 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 Dáša Longman. The network helps show where Dáša Longman may publish in the future.
Co-authors
The 25 scholars most cited alongside Dáša Longman, 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 | 2016 | 340 | |
| 2 | 2007 | 137 | |
| 3 | 2000 | 135 | |
| 4 | 2003 | 85 | |
| 5 | 2002 | 69 | |
| 6 | 2013 | 68 | |
| 7 | 2011 | 58 | |
| 8 | 2003 | 57 | |
| 9 | 2023 | 47 | |
| 10 | 2001 | 40 | |
| 11 | 2020 | 39 | |
| 12 | 2016 | 37 | |
| 13 | 2003 | 35 | |
| 14 | 2005 | 27 | |
| 15 | 2014 | 23 | |
| 16 | 2007 | 19 | |
| 17 | 2022 | 10 | |
| 18 | 2008 | 3 |
About Dáša Longman
Dáša Longman is a scholar working on Molecular Biology, Aging, Genetics, Genetics and Oncology, having authored 18 papers that have together received 1.2k indexed citations. Recurring topics across this work include RNA Research and Splicing (15 papers), RNA and protein synthesis mechanisms (7 papers), RNA modifications and cancer (5 papers), CRISPR and Genetic Engineering (5 papers), Genetics, Aging, and Longevity in Model Organisms (5 papers), RNA regulation and disease (4 papers), Peptidase Inhibition and Analysis (1 paper) and Connective tissue disorders research (1 paper). The work is most often cited by research in Aging (75 citations), Molecular Biology (1.1k citations), Genetics (158 citations), Cancer Research (82 citations) and Cell Biology (72 citations). Dáša Longman has collaborated with scholars based in United Kingdom, Canada and Germany. Frequent co-authors include Javier F. Cáceres, Nele Hug, Iain L. Johnstone, Ronald H.A. Plasterk, Corina Anastasaki, E. Elizabeth Patton, Jeremy R. Sanford, Susan McCracken, Benjamin J. Blencowe and Graeme R. Grimes. Their work appears in journals such as Nucleic Acids Research, Genes & Development, The EMBO Journal, Journal of Biological Chemistry and RNA.
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.