Nasa Sinnott-Armstrong
- Molecular Biology top 10%
- Genetics top 2%
- Infectious Diseases top 5%
- Biomedical Engineering
- Cancer Research
- Co-authors
- Manuel A. RivasJonathan K. PritchardAnshul KundajeMichael WainbergThomas QuertermousJohan BjörkegrenKe HaoNicholas Mancuso
- Topics
- Genetic Associations and Epidemiology (12 papers)RNA modifications and cancer (6 papers)Metabolomics and Mass Spectrometry Studies (5 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Nasa Sinnott-Armstrong
32 papers receiving 2.1k citations
Hit Papers
Peers
Comparison fields: 5 of 144
- Molecular Biology 1.1k
- Genetics 755
- Infectious Diseases 350
- Biomedical Engineering 251
- Cancer Research 150
Countries citing papers authored by Nasa Sinnott-Armstrong
This map shows the geographic impact of Nasa Sinnott-Armstrong'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 Nasa Sinnott-Armstrong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nasa Sinnott-Armstrong more than expected).
Fields of papers citing papers by Nasa Sinnott-Armstrong
This network shows the impact of papers produced by Nasa Sinnott-Armstrong. 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 Nasa Sinnott-Armstrong. The network helps show where Nasa Sinnott-Armstrong may publish in the future.
Co-authorship network of co-authors of Nasa Sinnott-Armstrong
This figure shows the co-authorship network connecting the top 25 collaborators of Nasa Sinnott-Armstrong. A scholar is included among the top collaborators of Nasa Sinnott-Armstrong based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nasa Sinnott-Armstrong. Nasa Sinnott-Armstrong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 8 | |
| 3 | 2 | |
| 4 | 10 | |
| 5 | 32 | |
| 6 | 17 | |
| 7 | 11 | |
| 8 | 33 | |
| 9 | 37 | |
| 10 | 62 | |
| 11 | 27 | |
| 12 | 34 | |
| 13 | 13 | |
| 14 | 103 | |
| 15 | 149 | |
| 16 | 21 | |
| 17 | 47 | |
| 18 | Opportunities and challenges for transcriptome-wide association studiesbreakdown → | 506 |
| 19 | 209 | |
| 20 | 28 |
About Nasa Sinnott-Armstrong
Nasa Sinnott-Armstrong is a scholar working on Health Informatics, Genetics and Molecular Biology, having authored 32 papers that have together received 2.1k indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (12 papers), RNA modifications and cancer (6 papers) and Metabolomics and Mass Spectrometry Studies (5 papers). The work is most often cited by research in Genetics (755 citations), Infectious Diseases (350 citations) and Molecular Biology (1.1k citations). Nasa Sinnott-Armstrong has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Manuel A. Rivas, Jonathan K. Pritchard, Anshul Kundaje, Michael Wainberg, Thomas Quertermous, Johan Björkegren, Ke Hao, Nicholas Mancuso, Arno Ruusalepp and Raili Ermel. Their work appears in journals such as Nature, Science and Proceedings of the National Academy of Sciences.
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.