Dávid Bajusz
Impact in
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods
- Molecular Biology top 10%
- Protein Structure and Dynamics
- Metabolomics and Mass Spectrometry Studies
- Bioinformatics and Genomic Networks
Papers in
-
- Receptor Mechanisms and Signaling 4
- Protein Structure and Dynamics 4
- Bioinformatics and Genomic Networks 4
-
- Computational Drug Discovery Methods 26
- Co-authors
- Anita Rácz (25 shared papers)Károly Héberger (20 shared papers)György M. Keserű (30 shared papers)Ramón Alain Miranda‐Quintana (7 shared papers)György G. Ferenczy (10 shared papers)Gábor Lente (1 shared paper)József Kalmár (1 shared paper)M. P. Takács (1 shared paper)
- Journals
- Journal of Chemical Information and Modeling (8 papers)Journal of Cheminformatics (4 papers)Molecules (4 papers)Journal of Medicinal Chemistry (3 papers)Molecular Informatics (2 papers)
- Partner nations
- HungaryUnited StatesPoland
In The Last Decade
Dávid Bajusz
54 papers receiving 2.6k citations
Dávid Bajusz's Hit Papers
Peers
Comparison fields: 5 of 178
- Computational Theory and Mathematics 1.1k
- Molecular Biology 1.0k
- Water Science and Technology 201
- Analytical Chemistry 126
- Spectroscopy 188
Countries citing papers authored by Dávid Bajusz
This map shows the geographic impact of Dávid Bajusz'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 Dávid Bajusz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dávid Bajusz more than expected).
Fields of papers citing papers by Dávid Bajusz
This network shows the impact of papers produced by Dávid Bajusz. 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 Dávid Bajusz. The network helps show where Dávid Bajusz may publish in the future.
Co-authors
The 25 scholars most cited alongside Dávid Bajusz, 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 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Why is Tanimoto index an appropriate choice for fingerprint-based similarity calculations? Hit paper breakdown → | 2015 | 1022 |
| 2 | 2009 | 226 | |
| 3 | Effect of Dataset Size and Train/Test Split Ratios in QSAR/QSPR Multiclass Classification Hit paper breakdown → | 2021 | 213 |
| 4 | 2019 | 92 | |
| 5 | 2015 | 92 | |
| 6 | 2018 | 88 | |
| 7 | 2017 | 68 | |
| 8 | 2019 | 66 | |
| 9 | 2016 | 57 | |
| 10 | 2019 | 50 | |
| 11 | 2018 | 46 | |
| 12 | 2019 | 46 | |
| 13 | 2021 | 42 | |
| 14 | 2021 | 37 | |
| 15 | 2017 | 36 | |
| 16 | 2020 | 36 | |
| 17 | 2022 | 35 | |
| 18 | 2021 | 35 | |
| 19 | 2021 | 34 | |
| 20 | 2020 | 23 |
About Dávid Bajusz
Dávid Bajusz is a scholar working on Molecular Biology, Computational Theory and Mathematics, Oncology, Organic Chemistry and Genetics, having authored 56 papers that have together received 2.6k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (26 papers), Cytokine Signaling Pathways and Interactions (10 papers), Receptor Mechanisms and Signaling (4 papers), Monoclonal and Polyclonal Antibodies Research (4 papers), Click Chemistry and Applications (4 papers), Protein Structure and Dynamics (4 papers), Bioinformatics and Genomic Networks (4 papers) and Machine Learning in Materials Science (4 papers). The work is most often cited by research in Computational Theory and Mathematics (1.1k citations), Molecular Biology (1.0k citations), Water Science and Technology (201 citations), Analytical Chemistry (126 citations) and Spectroscopy (188 citations). Dávid Bajusz has collaborated with scholars based in Hungary, United States and Poland. Frequent co-authors include Anita Rácz, Károly Héberger, György M. Keserű, Ramón Alain Miranda‐Quintana, György G. Ferenczy, Gábor Lente, József Kalmár, M. P. Takács, István Fábián and Zsuzsa Baranyai. Their work appears in journals such as Journal of Chemical Information and Modeling, Journal of Cheminformatics, Molecules, Journal of Medicinal Chemistry and Molecular Informatics.
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.