Arvid Berg
Impact in
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- Computational Drug Discovery Methods
- Spectroscopy top 10%
- Analytical Chemistry and Chromatography
Papers in
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- Computational Drug Discovery Methods 5
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- Biomedical Text Mining and Ontologies 1
- Protein Structure and Dynamics 1
- Co-authors
- Ola Spjuth (7 shared papers)Jonathan Alvarsson (6 shared papers)Egon Willighagen (4 shared papers)Gilleain Torrance (2 shared papers)Christoph Steinbeck (2 shared papers)Stefan Kühn (2 shared papers)Lars Carlsson (2 shared papers)Miguel Rojas‐Chertó (1 shared paper)
- Journals
- Journal of Cheminformatics (4 papers)BMC Bioinformatics (1 paper)Frontiers in Pharmacology (1 paper)Bioinformatics (1 paper)
- Partner nations
- SwedenNetherlandsUnited Kingdom
In The Last Decade
Arvid Berg
7 papers receiving 500 citations
Arvid Berg's Hit Papers
Peers
Comparison fields: 5 of 92
- Computational Theory and Mathematics 293
- Spectroscopy 98
- Pharmacology 33
- Molecular Biology 254
- Pharmacology 46
Countries citing papers authored by Arvid Berg
This map shows the geographic impact of Arvid Berg'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 Arvid Berg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arvid Berg more than expected).
Fields of papers citing papers by Arvid Berg
This network shows the impact of papers produced by Arvid Berg. 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 Arvid Berg. The network helps show where Arvid Berg may publish in the future.
Co-authors
The 23 scholars most cited alongside Arvid Berg, 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 Chemistry Development Kit (CDK) v2.0: atom typing, depiction, molecular formulas, and substructure searching Hit paper breakdown → | 2017 | 375 |
| 2 | 2009 | 48 | |
| 3 | 2018 | 47 | |
| 4 | 2018 | 24 | |
| 5 | 2012 | 8 | |
| 6 | 2013 | 7 | |
| 7 | 2020 | 1 |
About Arvid Berg
Arvid Berg is a scholar working on Computational Theory and Mathematics, Molecular Biology, Materials Chemistry, Information Systems and Management and Environmental Chemistry, having authored 7 papers that have together received 510 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (5 papers), Machine Learning in Materials Science (2 papers), Scientific Computing and Data Management (1 paper), Analytical Chemistry and Chromatography (1 paper), Biomedical Text Mining and Ontologies (1 paper), Analytical Methods in Pharmaceuticals (1 paper), Chemistry and Chemical Engineering (1 paper) and Protein Structure and Dynamics (1 paper). The work is most often cited by research in Computational Theory and Mathematics (293 citations), Spectroscopy (98 citations), Pharmacology (33 citations), Molecular Biology (254 citations) and Pharmacology (46 citations). Arvid Berg has collaborated with scholars based in Sweden, Netherlands and United Kingdom. Frequent co-authors include Ola Spjuth, Jonathan Alvarsson, Egon Willighagen, Gilleain Torrance, Christoph Steinbeck, Stefan Kühn, Lars Carlsson, Miguel Rojas‐Chertó, John W. Mayfield and Tomáš Pluskal. Their work appears in journals such as Journal of Cheminformatics, BMC Bioinformatics, Frontiers in Pharmacology and 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.