Jörg Wicker
Impact in
- Pollution top 10%
- Pharmaceutical and Antibiotic Environmental Impacts
- Sensory Systems top 10%
- Olfactory and Sensory Function Studies
Papers in
-
- Anomaly Detection Techniques and Applications 5
- Machine Learning and Algorithms 4
- Machine Learning and Data Classification 4
- Algorithms and Data Compression 3
-
- Computational Drug Discovery Methods 5
- Co-authors
- Stefan Krämer (12 shared papers)Kathrin Fenner (5 shared papers)Martin Gütlein (2 shared papers)Emanuel Schmid (2 shared papers)Diogo A. R. S. Latino (2 shared papers)Bernhard Pfahringer (2 shared papers)Jonathan Williams (3 shared papers)Efstratios Bourtsoukidis (3 shared papers)
- Journals
- Journal of Cheminformatics (5 papers)Machine Learning (3 papers)Life Science Alliance (2 papers)Artificial Intelligence Review (1 paper)Bioinformatics (1 paper)
- Partner nations
- New ZealandGermanySwitzerland
In The Last Decade
Jörg Wicker
41 papers receiving 685 citations
Peers
Comparison fields: 5 of 112
- Pollution 140
- Sensory Systems 42
- Health, Toxicology and Mutagenesis 116
- Computational Mathematics 5
- Computational Theory and Mathematics 78
Countries citing papers authored by Jörg Wicker
This map shows the geographic impact of Jörg Wicker'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 Jörg Wicker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jörg Wicker more than expected).
Fields of papers citing papers by Jörg Wicker
This network shows the impact of papers produced by Jörg Wicker. 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 Jörg Wicker. The network helps show where Jörg Wicker may publish in the future.
Co-authors
The 25 scholars most cited alongside Jörg Wicker, 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 46 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 157 | |
| 2 | 2016 | 84 | |
| 3 | 2020 | 61 | |
| 4 | 2010 | 54 | |
| 5 | 2017 | 50 | |
| 6 | 2019 | 46 | |
| 7 | 2012 | 44 | |
| 8 | 2021 | 22 | |
| 9 | 2024 | 18 | |
| 10 | 2016 | 17 | |
| 11 | 2006 | 14 | |
| 12 | 2024 | 13 | |
| 13 | 2021 | 13 | |
| 14 | 2018 | 13 | |
| 15 | 2008 | 13 | |
| 16 | 2015 | 12 | |
| 17 | 2021 | 9 | |
| 18 | 2020 | 8 | |
| 19 | 2022 | 6 | |
| 20 | 2023 | 6 |
About Jörg Wicker
Jörg Wicker is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Molecular Biology, Computer Networks and Communications and Information Systems, having authored 46 papers that have together received 712 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (5 papers), Computational Drug Discovery Methods (5 papers), Data Mining Algorithms and Applications (4 papers), Machine Learning and Algorithms (4 papers), Machine Learning and Data Classification (4 papers), Olfactory and Sensory Function Studies (3 papers), Advanced Database Systems and Queries (3 papers) and Algorithms and Data Compression (3 papers). The work is most often cited by research in Pollution (140 citations), Sensory Systems (42 citations), Health, Toxicology and Mutagenesis (116 citations), Computational Mathematics (5 citations) and Computational Theory and Mathematics (78 citations). Jörg Wicker has collaborated with scholars based in New Zealand, Germany and Switzerland. Frequent co-authors include Stefan Krämer, Kathrin Fenner, Martin Gütlein, Emanuel Schmid, Diogo A. R. S. Latino, Bernhard Pfahringer, Jonathan Williams, Efstratios Bourtsoukidis, Christof Stönner and T. Klüpfel. Their work appears in journals such as Journal of Cheminformatics, Machine Learning, Life Science Alliance, Artificial Intelligence Review 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.