Nasa Sinnott-Armstrong
- Genetics top 2%
- Genetic Associations and Epidemiology 12
- Infectious Diseases top 5%
- SARS-CoV-2 detection and testing 4
- Molecular Biology top 10%
- RNA modifications and cancer 6
- Metabolomics and Mass Spectrometry Studies 5
- Genomics and Chromatin Dynamics 5
- Bioinformatics and Genomic Networks 4
- RNA Research and Splicing 3
- Health Informatics top 10%
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- Biosensors and Analytical Detection 3
- Co-authors
- Manuel A. RivasJonathan K. PritchardAnshul KundajeMichael WainbergThomas QuertermousJohan BjörkegrenKe HaoNicholas Mancuso
- Journals
- Nature (1 paper)Science (2 papers)Proceedings of the National Academy of Sciences (2 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
- Genetics 755
- Infectious Diseases 350
- Molecular Biology 1.1k
- Health Informatics 17
- 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
The 25 scholars most cited alongside Nasa Sinnott-Armstrong, 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 | 3 | |
| 2 | 2024 | 8 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 10 | |
| 5 | 2024 | 32 | |
| 6 | 2023 | 17 | |
| 7 | 2023 | 11 | |
| 8 | 2022 | 33 | |
| 9 | 2022 | 37 | |
| 10 | 2021 | 62 | |
| 11 | 2021 | 27 | |
| 12 | 2021 | 34 | |
| 13 | 2021 | 13 | |
| 14 | 2021 | 103 | |
| 15 | 2020 | 149 | |
| 16 | 2020 | 21 | |
| 17 | 2020 | 47 | |
| 18 | Opportunities and challenges for transcriptome-wide association studiesbreakdown → | 2019 | 506 |
| 19 | 2019 | 209 | |
| 20 | 2019 | 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), Metabolomics and Mass Spectrometry Studies (5 papers), Genomics and Chromatin Dynamics (5 papers), Bioinformatics and Genomic Networks (4 papers), SARS-CoV-2 detection and testing (4 papers), Biosensors and Analytical Detection (3 papers) and RNA Research and Splicing (3 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.