Mark N. Wass
Impact in
- Molecular Biology top 1%
- RNA and protein synthesis mechanisms
- Protein Structure and Dynamics
- Genomics and Phylogenetic Studies
- Photosynthetic Processes and Mechanisms
- Endocrinology top 1%
Papers in
-
- Viral Infections and Outbreaks Research 6
- COVID-19 Clinical Research Studies 5
- SARS-CoV-2 and COVID-19 Research 4
- Co-authors
- Michael J.E. SternbergLawrence A. KelleyChristopher M. YatesMartin MichaelisAlessia DavidJindřich ČinátlRozaimi RazaliPier Federico Gherardini
- Journals
- Bioinformatics (5 papers)Scientific Reports (4 papers)Cells (4 papers)Nucleic Acids Research (4 papers)Nature Communications (2 papers)
- Partner nations
- United KingdomGermanyUnited States
In The Last Decade
Mark N. Wass
66 papers receiving 9.4k citations
Hit Papers
Peers
Comparison fields: 5 of 162
- Molecular Biology 5.8k
- Endocrinology 351
- Biotechnology 509
- Molecular Medicine 279
- Microbiology 302
Countries citing papers authored by Mark N. Wass
This map shows the geographic impact of Mark N. Wass'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 Mark N. Wass with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark N. Wass more than expected).
Fields of papers citing papers by Mark N. Wass
This network shows the impact of papers produced by Mark N. Wass. 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 Mark N. Wass. The network helps show where Mark N. Wass may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mark N. Wass, 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 | 1 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 3 | |
| 4 | 2024 | 2 | |
| 5 | 2023 | 12 | |
| 6 | 2023 | 3 | |
| 7 | 2021 | 9 | |
| 8 | 2020 | 54 | |
| 9 | 2019 | 3 | |
| 10 | 2019 | 31 | |
| 11 | 2019 | 33 | |
| 12 | 2019 | 27 | |
| 13 | 2019 | 44 | |
| 14 | 2017 | 16 | |
| 15 | 2015 | 71 | |
| 16 | 2014 | 41 | |
| 17 | 2014 | 17 | |
| 18 | 2012 | 31 | |
| 19 | 2011 | 65 | |
| 20 | 1980 | 16 |
About Mark N. Wass
Mark N. Wass is a scholar working on Modeling and Simulation, Infectious Diseases, Biophysics, Molecular Biology and Neurology, having authored 68 papers that have together received 9.5k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (8 papers), Cancer therapeutics and mechanisms (7 papers), Machine Learning in Bioinformatics (6 papers), Viral Infections and Outbreaks Research (6 papers), Bioinformatics and Genomic Networks (6 papers), Neuroblastoma Research and Treatments (5 papers), COVID-19 Clinical Research Studies (5 papers) and SARS-CoV-2 and COVID-19 Research (4 papers). The work is most often cited by research in Molecular Biology (5.8k citations), Endocrinology (351 citations), Biotechnology (509 citations), Molecular Medicine (279 citations) and Microbiology (302 citations). Mark N. Wass has collaborated with scholars based in United Kingdom, Germany and United States. Frequent co-authors include Michael J.E. Sternberg, Lawrence A. Kelley, Christopher M. Yates, Martin Michaelis, Alessia David, Jindřich Činátl, Rozaimi Razali, Pier Federico Gherardini, Manuela Helmer‐Citterich and Arthur M. Talman. Their work appears in journals such as Bioinformatics, Scientific Reports, Cells, Nucleic Acids Research and Nature Communications.
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.