David B. Blumenthal
Impact in
- Health Informatics top 10%
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- Computational Drug Discovery Methods
Papers in
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- Bioinformatics and Genomic Networks 19
- Gene expression and cancer classification 9
- Gene Regulatory Network Analysis 5
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- Computational Drug Discovery Methods 10
- Co-authors
- Johann Gamper (9 shared papers)Markus List (18 shared papers)Jan Baumbach (20 shared papers)Tim Kacprowski (11 shared papers)Olga Lazareva (6 shared papers)Luc Brun (5 shared papers)Sébastien Bougleux (6 shared papers)Sepideh Sadegh (6 shared papers)
In The Last Decade
David B. Blumenthal
37 papers receiving 527 citations
Peers
Comparison fields: 5 of 120
- Health Informatics 22
- Computational Theory and Mathematics 112
- Signal Processing 58
- Artificial Intelligence 169
- Computer Vision and Pattern Recognition 105
Countries citing papers authored by David B. Blumenthal
This map shows the geographic impact of David B. Blumenthal'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. Blumenthal 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. Blumenthal more than expected).
Fields of papers citing papers by David B. Blumenthal
This network shows the impact of papers produced by David B. Blumenthal. 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. Blumenthal. The network helps show where David B. Blumenthal may publish in the future.
Co-authors
The 25 scholars most cited alongside David B. Blumenthal, 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 48 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 86 | |
| 2 | 2018 | 54 | |
| 3 | 2022 | 50 | |
| 4 | 2020 | 41 | |
| 5 | 2024 | 33 | |
| 6 | 2024 | 29 | |
| 7 | 2021 | 29 | |
| 8 | 2019 | 24 | |
| 9 | 2021 | 17 | |
| 10 | 2017 | 16 | |
| 11 | 2021 | 16 | |
| 12 | 2020 | 15 | |
| 13 | 2020 | 14 | |
| 14 | 2020 | 10 | |
| 15 | 2023 | 10 | |
| 16 | 2025 | 10 | |
| 17 | 2023 | 8 | |
| 18 | 2018 | 8 | |
| 19 | 2020 | 7 | |
| 20 | 2019 | 7 |
About David B. Blumenthal
David B. Blumenthal is a scholar working on Molecular Biology, Computational Theory and Mathematics, Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 48 papers that have together received 544 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (19 papers), Computational Drug Discovery Methods (10 papers), Gene expression and cancer classification (9 papers), Graph Theory and Algorithms (8 papers), Advanced Graph Neural Networks (7 papers), Data Management and Algorithms (5 papers), Gene Regulatory Network Analysis (5 papers) and Optimization and Search Problems (4 papers). The work is most often cited by research in Health Informatics (22 citations), Computational Theory and Mathematics (112 citations), Signal Processing (58 citations), Artificial Intelligence (169 citations) and Computer Vision and Pattern Recognition (105 citations). David B. Blumenthal has collaborated with scholars based in Germany, Italy and Denmark. Frequent co-authors include Johann Gamper, Markus List, Jan Baumbach, Tim Kacprowski, Olga Lazareva, Luc Brun, Sébastien Bougleux, Sepideh Sadegh, Reihaneh Torkzadehmahani and Ulf Leser. Their work appears in journals such as Bioinformatics, Briefings in Bioinformatics, Nature Communications, Pattern Recognition Letters and The VLDB 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.