Daniel Muthas
Impact in
-
- Computational Drug Discovery Methods
-
- IL-33, ST2, and ILC Pathways
Papers in ⓘ
- Aging 1
- Co-authors
- Anders Karlén (8 shared papers)Scott Boyer (3 shared papers)Yogesh Sabnis (2 shared papers)Aurijit Sarkar (1 shared paper)Ruth Brenk (1 shared paper)Stefan Schmitt (1 shared paper)Silvio Danese (1 shared paper)Mohib Uddin (1 shared paper)
- Journals
- Annals of the Rheumatic Diseases (3 papers)Respiratory Research (2 papers)MedChemComm (2 papers)Bioorganic & Medicinal Chemistry (2 papers)Journal of Peptide Science (2 papers)
- Partner nations
- SwedenUnited KingdomUnited States
In The Last Decade
Daniel Muthas
33 papers receiving 840 citations
Peers
Comparison fields: 5 of 101
- Computational Theory and Mathematics 178
- Immunology 181
- Pharmacology 70
- Organic Chemistry 199
- Infectious Diseases 88
Countries citing papers authored by Daniel Muthas
This map shows the geographic impact of Daniel Muthas'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 Muthas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Muthas more than expected).
Fields of papers citing papers by Daniel Muthas
This network shows the impact of papers produced by Daniel Muthas. 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 Muthas. The network helps show where Daniel Muthas may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Muthas, 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 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 141 | |
| 2 | 2007 | 78 | |
| 3 | 2009 | 78 | |
| 4 | 2013 | 74 | |
| 5 | 2019 | 71 | |
| 6 | 2011 | 68 | |
| 7 | 2007 | 47 | |
| 8 | 2020 | 34 | |
| 9 | 2024 | 32 | |
| 10 | 2012 | 31 | |
| 11 | 2013 | 31 | |
| 12 | 2005 | 30 | |
| 13 | 2007 | 24 | |
| 14 | 2021 | 23 | |
| 15 | 2019 | 17 | |
| 16 | 2011 | 17 | |
| 17 | 2020 | 13 | |
| 18 | 2013 | 11 | |
| 19 | 2010 | 7 | |
| 20 | 2013 | 7 |
About Daniel Muthas
Daniel Muthas is a scholar working on Aging, Pharmacology, Immunology, Computational Theory and Mathematics and Rheumatology, having authored 33 papers that have together received 863 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (6 papers), IL-33, ST2, and ILC Pathways (6 papers), Cancer therapeutics and mechanisms (5 papers), Tuberculosis Research and Epidemiology (5 papers), Asthma and respiratory diseases (4 papers), Protein Structure and Dynamics (3 papers), Biochemical and Molecular Research (3 papers) and Eosinophilic Esophagitis (3 papers). The work is most often cited by research in Computational Theory and Mathematics (178 citations), Immunology (181 citations), Pharmacology (70 citations), Organic Chemistry (199 citations) and Infectious Diseases (88 citations). Daniel Muthas has collaborated with scholars based in Sweden, United Kingdom and United States. Frequent co-authors include Anders Karlén, Scott Boyer, Yogesh Sabnis, Aurijit Sarkar, Ruth Brenk, Stefan Schmitt, Silvio Danese, Mohib Uddin, Luke R. Odell and Gerhard Böttcher. Their work appears in journals such as Annals of the Rheumatic Diseases, Respiratory Research, MedChemComm, Bioorganic & Medicinal Chemistry and Journal of Peptide Science.
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.