David B. Ascher
Impact in
- Computational Theory and Mathematics top 0.1%
- Computational Drug Discovery Methods
- Molecular Biology top 0.5%
- Protein Structure and Dynamics
- RNA and protein synthesis mechanisms
- vaccines and immunoinformatics approaches
Papers in
-
- Computational Drug Discovery Methods 33
-
- Protein Structure and Dynamics 36
- RNA and protein synthesis mechanisms 24
- Bioinformatics and Genomic Networks 16
- Biochemical and Molecular Research 14
- Co-authors
- Douglas E. V. PiresTom L. BlundellCarlos H. M. RodriguesT.L. BlundellYoochan MyungBernardo Ochoa‐MontañoArun Prasad PanduranganHarry Jubb
- Journals
- Nucleic Acids Research (20 papers)Briefings in Bioinformatics (11 papers)Scientific Reports (9 papers)Protein Science (9 papers)Computational and Structural Biotechnology Journal (7 papers)
- Partner nations
- AustraliaUnited KingdomBrazil
In The Last Decade
David B. Ascher
181 papers receiving 11.7k citations
Hit Papers
Peers
Comparison fields: 5 of 174
- Computational Theory and Mathematics 2.6k
- Molecular Biology 6.9k
- Infectious Diseases 1.4k
- Pharmacology 555
- Toxicology 208
Countries citing papers authored by David B. Ascher
This map shows the geographic impact of David B. Ascher'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 David B. Ascher with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David B. Ascher more than expected).
Fields of papers citing papers by David B. Ascher
This network shows the impact of papers produced by David B. Ascher. 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 David B. Ascher. The network helps show where David B. Ascher may publish in the future.
Co-authors
The 25 scholars most cited alongside David B. Ascher, 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 | 0 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 4 | |
| 4 | 2024 | 1 | |
| 5 | DDMut: predicting effects of mutations on protein stability using deep learning Hit paper breakdown → | 2023 | 100 |
| 6 | 2023 | 37 | |
| 7 | 2023 | 10 | |
| 8 | 2022 | 23 | |
| 9 | 2021 | 11 | |
| 10 | 2021 | 14 | |
| 11 | 2020 | 40 | |
| 12 | 2019 | 51 | |
| 13 | 2019 | 24 | |
| 14 | 2018 | 68 | |
| 15 | 2018 | 38 | |
| 16 | 2018 | 31 | |
| 17 | 2018 | 24 | |
| 18 | 2017 | 140 | |
| 19 | 2017 | 90 | |
| 20 | 2017 | 48 |
About David B. Ascher
David B. Ascher is a scholar working on Computational Theory and Mathematics, Molecular Biology, Infectious Diseases, Virology and Molecular Medicine, having authored 187 papers that have together received 11.8k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (36 papers), Computational Drug Discovery Methods (33 papers), RNA and protein synthesis mechanisms (24 papers), Bioinformatics and Genomic Networks (16 papers), Genomics and Rare Diseases (14 papers), Biochemical and Molecular Research (14 papers), Tuberculosis Research and Epidemiology (13 papers) and Enzyme Structure and Function (12 papers). The work is most often cited by research in Computational Theory and Mathematics (2.6k citations), Molecular Biology (6.9k citations), Infectious Diseases (1.4k citations), Pharmacology (555 citations) and Toxicology (208 citations). David B. Ascher has collaborated with scholars based in Australia, United Kingdom and Brazil. Frequent co-authors include Douglas E. V. Pires, Tom L. Blundell, Carlos H. M. Rodrigues, T.L. Blundell, Yoochan Myung, Bernardo Ochoa‐Montaño, Arun Prasad Pandurangan, Harry Jubb, Michael W. Parker and Lisa M. Kaminskas. Their work appears in journals such as Nucleic Acids Research, Briefings in Bioinformatics, Scientific Reports, Protein Science and Computational and Structural Biotechnology Journal.
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.