Daniel Korn
Impact in
-
- Computational Drug Discovery Methods
Papers in ⓘ
-
- Computational Drug Discovery Methods 12
-
- Animal testing and alternatives 3
- Co-authors
- Alexander Tropsha (20 shared papers)Eugene Muratov (16 shared papers)Vinícius M. Alves (13 shared papers)Tesia Bobrowski (6 shared papers)Carolina Horta Andrade (3 shared papers)Rodolpho C. Braga (4 shared papers)Cleber C. Melo‐Filho (5 shared papers)Charles Schmitt (4 shared papers)
- Journals
- Journal of Chemical Information and Modeling (4 papers)Drug Discovery Today (3 papers)Bioinformatics (3 papers)Blood (1 paper)BMC Bioinformatics (1 paper)
- Partner nations
- United StatesBrazilCanada
In The Last Decade
Daniel Korn
20 papers receiving 365 citations
Hit Papers
Peers
Comparison fields: 5 of 103
- Computational Theory and Mathematics 200
- Health Informatics 5
- Infectious Diseases 68
- Chemical Health and Safety 2
- Small Animals 21
Countries citing papers authored by Daniel Korn
This map shows the geographic impact of Daniel Korn'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 Korn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Korn more than expected).
Fields of papers citing papers by Daniel Korn
This network shows the impact of papers produced by Daniel Korn. 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 Korn. The network helps show where Daniel Korn may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Korn, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | STopTox: An in Silico Alternative to Animal Testing for Acute Systemic and Topical Toxicity Hit paper breakdown → | 2022 | 122 |
| 2 | 2020 | 63 | |
| 3 | 2018 | 40 | |
| 4 | 2020 | 27 | |
| 5 | 2021 | 26 | |
| 6 | 2020 | 25 | |
| 7 | 2020 | 15 | |
| 8 | 2022 | 9 | |
| 9 | 2023 | 7 | |
| 10 | 2022 | 6 | |
| 11 | 2021 | 6 | |
| 12 | 2021 | 4 | |
| 13 | Cannibal: The History of the People-eaters | 2001 | 4 |
| 14 | 2022 | 3 | |
| 15 | 2022 | 3 | |
| 16 | 2021 | 3 | |
| 17 | 2023 | 3 | |
| 18 | 2024 | 2 | |
| 19 | 2025 | 1 | |
| 20 | 2024 | 1 |
About Daniel Korn
Daniel Korn is a scholar working on Computational Theory and Mathematics, Small Animals, Infectious Diseases, Molecular Biology and Genetics, having authored 26 papers that have together received 370 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (12 papers), Bioinformatics and Genomic Networks (6 papers), Biomedical Text Mining and Ontologies (5 papers), Genomics and Rare Diseases (4 papers), Animal testing and alternatives (3 papers), Advanced Graph Neural Networks (3 papers), Tuberculosis Research and Epidemiology (2 papers) and Semantic Web and Ontologies (2 papers). The work is most often cited by research in Computational Theory and Mathematics (200 citations), Health Informatics (5 citations), Infectious Diseases (68 citations), Chemical Health and Safety (2 citations) and Small Animals (21 citations). Daniel Korn has collaborated with scholars based in United States, Brazil and Canada. Frequent co-authors include Alexander Tropsha, Eugene Muratov, Vinícius M. Alves, Tesia Bobrowski, Carolina Horta Andrade, Rodolpho C. Braga, Cleber C. Melo‐Filho, Charles Schmitt, Scott S. Auerbach and Joyce Villa Verde Bastos Borba. Their work appears in journals such as Journal of Chemical Information and Modeling, Drug Discovery Today, Bioinformatics, Blood and BMC Bioinformatics.
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.