Daniel Arend
Impact in
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- Scientific Computing and Data Management
- Plant Science top 10%
- Wheat and Barley Genetics and Pathology
- Genetics and Plant Breeding
- Smart Agriculture and AI
Papers in
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- Research Data Management Practices 10
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- Scientific Computing and Data Management 10
- Co-authors
- Uwe Scholz (12 shared papers)Matthias Lange (14 shared papers)Astrid Junker (5 shared papers)Danuta Schüler (4 shared papers)Jinbo Chen (1 shared paper)Andreas Graner (3 shared papers)Christian Colmsee (2 shared papers)Jean-Michel Pape (1 shared paper)
In The Last Decade
Daniel Arend
19 papers receiving 371 citations
Peers
Comparison fields: 5 of 53
- Information Systems and Management 56
- Plant Science 241
- Genetics 118
- Horticulture 4
- Ecological Modeling 17
Countries citing papers authored by Daniel Arend
This map shows the geographic impact of Daniel Arend'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 Daniel Arend with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Arend more than expected).
Fields of papers citing papers by Daniel Arend
This network shows the impact of papers produced by Daniel Arend. 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 Daniel Arend. The network helps show where Daniel Arend may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Arend, 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 | 2016 | 71 | |
| 2 | 2014 | 69 | |
| 3 | 2018 | 62 | |
| 4 | 2018 | 42 | |
| 5 | 2020 | 23 | |
| 6 | 2022 | 21 | |
| 7 | 2017 | 21 | |
| 8 | 2019 | 14 | |
| 9 | 2018 | 13 | |
| 10 | 2021 | 12 | |
| 11 | 2020 | 9 | |
| 12 | 2019 | 7 | |
| 13 | 2017 | 7 | |
| 14 | 2022 | 2 | |
| 15 | 2024 | 2 | |
| 16 | 2023 | 1 | |
| 17 | 2025 | 1 | |
| 18 | 2023 | 1 | |
| 19 | 2012 | 1 |
About Daniel Arend
Daniel Arend is a scholar working on Information Systems, Information Systems and Management, Molecular Biology, Genetics and Plant Science, having authored 19 papers that have together received 379 indexed citations. Recurring topics across this work include Scientific Computing and Data Management (10 papers), Research Data Management Practices (10 papers), Genetic Mapping and Diversity in Plants and Animals (7 papers), Wheat and Barley Genetics and Pathology (4 papers), Genomics and Phylogenetic Studies (4 papers), Biomedical Text Mining and Ontologies (2 papers), Gene expression and cancer classification (2 papers) and Genetics, Bioinformatics, and Biomedical Research (1 paper). The work is most often cited by research in Information Systems and Management (56 citations), Plant Science (241 citations), Genetics (118 citations), Horticulture (4 citations) and Ecological Modeling (17 citations). Daniel Arend has collaborated with scholars based in Germany, Australia and Spain. Frequent co-authors include Uwe Scholz, Matthias Lange, Astrid Junker, Danuta Schüler, Jinbo Chen, Andreas Graner, Christian Colmsee, Jean-Michel Pape, Christian Klukas and Dijun Chen. Their work appears in journals such as Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics, Journal of Biotechnology, Scientific Data, Frontiers in Plant Science and GigaScience.
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.