Jörg Wicker
Impact in
- Pollution top 10%
- Pharmaceutical and Antibiotic Environmental Impacts
- Pesticide and Herbicide Environmental Studies
-
- Indoor Air Quality and Microbial Exposure
Papers in
-
- Machine Learning and Data Classification 3
- Anomaly Detection Techniques and Applications 3
- Text and Document Classification Technologies 2
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- Computational Drug Discovery Methods 6
- Co-authors
- Stefan Krämer (7 shared papers)Kathrin Fenner (4 shared papers)Martin Gütlein (2 shared papers)Diogo A. R. S. Latino (2 shared papers)Emanuel Schmid (2 shared papers)Jonathan Williams (3 shared papers)Efstratios Bourtsoukidis (3 shared papers)Christof Stönner (3 shared papers)
- Journals
- Journal of Cheminformatics (5 papers)Machine Learning (3 papers)Life Science Alliance (2 papers)Scientific Reports (1 paper)Data Mining and Knowledge Discovery (1 paper)
- Partner nations
- New ZealandGermanySwitzerland
In The Last Decade
Jörg Wicker
30 papers receiving 521 citations
Peers
Comparison fields: 5 of 108
- Pollution 121
- Health, Toxicology and Mutagenesis 106
- Sensory Systems 35
- Computational Theory and Mathematics 73
- Environmental Chemistry 38
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 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 139 | |
| 2 | 2016 | 74 | |
| 3 | 2020 | 57 | |
| 4 | 2010 | 47 | |
| 5 | 2017 | 41 | |
| 6 | 2019 | 40 | |
| 7 | 2012 | 31 | |
| 8 | 2021 | 21 | |
| 9 | 2021 | 12 | |
| 10 | 2018 | 11 | |
| 11 | 2024 | 9 | |
| 12 | 2021 | 9 | |
| 13 | 2015 | 9 | |
| 14 | 2024 | 8 | |
| 15 | 2023 | 5 | |
| 16 | 2022 | 5 | |
| 17 | 2020 | 4 | |
| 18 | 2023 | 3 | |
| 19 | 2020 | 3 | |
| 20 | 2022 | 3 |
About Jörg Wicker
Jörg Wicker is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Molecular Biology, Computer Vision and Pattern Recognition and Sensory Systems, having authored 32 papers that have together received 545 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (6 papers), Machine Learning and Data Classification (3 papers), Anomaly Detection Techniques and Applications (3 papers), Advanced Chemical Sensor Technologies (3 papers), Olfactory and Sensory Function Studies (3 papers), Analytical Chemistry and Chromatography (2 papers), Text and Document Classification Technologies (2 papers) and Mobile Crowdsensing and Crowdsourcing (2 papers). The work is most often cited by research in Pollution (121 citations), Health, Toxicology and Mutagenesis (106 citations), Sensory Systems (35 citations), Computational Theory and Mathematics (73 citations) and Environmental Chemistry (38 citations). Jörg Wicker has collaborated with scholars based in New Zealand, Germany and Switzerland. Frequent co-authors include Stefan Krämer, Kathrin Fenner, Martin Gütlein, Diogo A. R. S. Latino, Emanuel Schmid, Jonathan Williams, Efstratios Bourtsoukidis, Christof Stönner, T. Klüpfel and Bettina Derstroff. Their work appears in journals such as Journal of Cheminformatics, Machine Learning, Life Science Alliance, Scientific Reports and Data Mining and Knowledge Discovery.
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.