Jörg Ackermann
Impact in
- Clinical Biochemistry top 10%
-
- Mitochondrial Function and Pathology
- Gene Regulatory Network Analysis
- ATP Synthase and ATPases Research
- Microbial Metabolic Engineering and Bioproduction
- Bioinformatics and Genomic Networks
- Advanced biosensing and bioanalysis techniques
- RNA and protein synthesis mechanisms
- DNA and Biological Computing
Papers in
-
- Gene Regulatory Network Analysis 14
- Microbial Metabolic Engineering and Bioproduction 10
- Bioinformatics and Genomic Networks 10
-
- AI in cancer detection 7
- Co-authors
- Ina Koch (40 shared papers)Robert Penchovsky (1 shared paper)Ilka Wittig (4 shared papers)Stefan Dröse (2 shared papers)Lea Bleier (2 shared papers)Ulrich Brandt (3 shared papers)Heinrich Heide (2 shared papers)Bettina Schwamb (1 shared paper)
- Journals
- Bioinformatics (6 papers)PLoS Computational Biology (4 papers)BMC Bioinformatics (3 papers)Biological Chemistry (2 papers)Biosystems (2 papers)
- Partner nations
- GermanySwitzerlandAustria
In The Last Decade
Jörg Ackermann
49 papers receiving 801 citations
Peers
Comparison fields: 5 of 110
- Clinical Biochemistry 63
- Molecular Biology 588
- Health Informatics 6
- Biophysics 25
- Modeling and Simulation 20
Countries citing papers authored by Jörg Ackermann
This map shows the geographic impact of Jörg Ackermann'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 Ackermann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jörg Ackermann more than expected).
Fields of papers citing papers by Jörg Ackermann
This network shows the impact of papers produced by Jörg Ackermann. 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 Ackermann. The network helps show where Jörg Ackermann may publish in the future.
Co-authors
The 25 scholars most cited alongside Jörg Ackermann, 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 50 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 224 | |
| 2 | 2003 | 64 | |
| 3 | 2014 | 63 | |
| 4 | 2008 | 52 | |
| 5 | 2021 | 23 | |
| 6 | 2023 | 22 | |
| 7 | 2016 | 20 | |
| 8 | 1998 | 20 | |
| 9 | 2013 | 19 | |
| 10 | 2016 | 17 | |
| 11 | 2023 | 17 | |
| 12 | 2005 | 16 | |
| 13 | 2015 | 16 | |
| 14 | 2021 | 15 | |
| 15 | 2001 | 14 | |
| 16 | 2013 | 13 | |
| 17 | 2015 | 13 | |
| 18 | 2020 | 12 | |
| 19 | 2023 | 12 | |
| 20 | 2020 | 12 |
About Jörg Ackermann
Jörg Ackermann is a scholar working on Molecular Biology, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Genetics and Oncology, having authored 50 papers that have together received 812 indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (14 papers), Microbial Metabolic Engineering and Bioproduction (10 papers), Bioinformatics and Genomic Networks (10 papers), Radiomics and Machine Learning in Medical Imaging (9 papers), AI in cancer detection (7 papers), Cell Image Analysis Techniques (4 papers), Advanced X-ray and CT Imaging (4 papers) and Evolution and Genetic Dynamics (3 papers). The work is most often cited by research in Clinical Biochemistry (63 citations), Molecular Biology (588 citations), Health Informatics (6 citations), Biophysics (25 citations) and Modeling and Simulation (20 citations). Jörg Ackermann has collaborated with scholars based in Germany, Switzerland and Austria. Frequent co-authors include Ina Koch, Robert Penchovsky, Ilka Wittig, Stefan Dröse, Lea Bleier, Ulrich Brandt, Heinrich Heide, Bettina Schwamb, Andreas S. Reichert and Martin Zörnig. Their work appears in journals such as Bioinformatics, PLoS Computational Biology, BMC Bioinformatics, Biological Chemistry and Biosystems.
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.