Ines Šmit
Impact in
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods
- Pharmacology top 5%
- Microbial Natural Products and Biosynthesis
- Pharmacogenetics and Drug Metabolism
Papers in
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- Computational Drug Discovery Methods 8
-
- Pharmacogenetics and Drug Metabolism 3
- Co-authors
- Francis L. Atkinson (2 shared papers)María Paula Magariños (2 shared papers)Andrew R. Leach (3 shared papers)A. Patrícia Bento (2 shared papers)Prudence Mutowo (1 shared paper)Michał Nowotka (1 shared paper)Elena Cibrián–Uhalte (1 shared paper)Anneli Karlsson (1 shared paper)
- Journals
- Chemical Research in Toxicology (2 papers)Nucleic Acids Research (2 papers)Basic & Clinical Pharmacology & Toxicology (1 paper)npj Systems Biology and Applications (1 paper)Journal of Medicinal Chemistry (1 paper)
- Partner nations
- United KingdomGermanySweden
In The Last Decade
Ines Šmit
9 papers receiving 2.0k citations
Ines Šmit's Hit Papers
Peers
Comparison fields: 5 of 128
- Computational Theory and Mathematics 1.2k
- Pharmacology 160
- Pharmacology 277
- Molecular Biology 1.1k
- Biophysics 49
Countries citing papers authored by Ines Šmit
This map shows the geographic impact of Ines Šmit'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 Ines Šmit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ines Šmit more than expected).
Fields of papers citing papers by Ines Šmit
This network shows the impact of papers produced by Ines Šmit. 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 Ines Šmit. The network helps show where Ines Šmit may publish in the future.
Co-authors
The 25 scholars most cited alongside Ines Šmit, 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 | The ChEMBL database in 2017 Hit paper breakdown → | 2016 | 1822 |
| 2 | Open Targets Platform: facilitating therapeutic hypotheses building in drug discovery Hit paper breakdown → | 2024 | 82 |
| 3 | 2020 | 34 | |
| 4 | 2014 | 23 | |
| 5 | 2018 | 20 | |
| 6 | 2020 | 19 | |
| 7 | 2017 | 13 | |
| 8 | 2025 | 6 | |
| 9 | 2018 | 5 | |
| 10 | 2026 | 0 | |
| 11 | 2024 | 0 |
About Ines Šmit
Ines Šmit is a scholar working on Computational Theory and Mathematics, Pharmacology, Molecular Biology, Toxicology and Cardiology and Cardiovascular Medicine, having authored 11 papers that have together received 2.0k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (8 papers), Pharmacogenetics and Drug Metabolism (3 papers), Bioinformatics and Genomic Networks (2 papers), Receptor Mechanisms and Signaling (2 papers), Cardiovascular Function and Risk Factors (1 paper), Biomedical Text Mining and Ontologies (1 paper), Chemotherapy-induced cardiotoxicity and mitigation (1 paper) and Meta-analysis and systematic reviews (1 paper). The work is most often cited by research in Computational Theory and Mathematics (1.2k citations), Pharmacology (160 citations), Pharmacology (277 citations), Molecular Biology (1.1k citations) and Biophysics (49 citations). Ines Šmit has collaborated with scholars based in United Kingdom, Germany and Sweden. Frequent co-authors include Francis L. Atkinson, María Paula Magariños, Andrew R. Leach, A. Patrícia Bento, Prudence Mutowo, Michał Nowotka, Elena Cibrián–Uhalte, Anneli Karlsson, Anna Gaulton and David Méndez. Their work appears in journals such as Chemical Research in Toxicology, Nucleic Acids Research, Basic & Clinical Pharmacology & Toxicology, npj Systems Biology and Applications and Journal of Medicinal Chemistry.
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.