Axel Facius
Impact in
-
- Gene expression and cancer classification
- Bioinformatics and Genomic Networks
- Machine Learning in Bioinformatics
- Genomics and Phylogenetic Studies
- Artificial Intelligence top 10%
- Evolutionary Algorithms and Applications
Papers in
-
- Bioinformatics and Genomic Networks 4
- Genomics and Phylogenetic Studies 3
- Machine Learning in Bioinformatics 1
- Microbial Metabolic Engineering and Bioproduction 1
- Metabolomics and Mass Spectrometry Studies 1
- Molecular Biology Techniques and Applications 1
-
- Advanced Proteomics Techniques and Applications 2
- Co-authors
- Klaus Mayer (2 shared papers)Igor V. Tetko (2 shared papers)Hans‐Werner Mewes (3 shared papers)Eibe Frank (1 shared paper)Yu Wang (1 shared paper)Mark A. Hall (1 shared paper)Andreas Graner (1 shared paper)Thomas Thiel (1 shared paper)
- Journals
- Molecular Genetics and Genomics (1 paper)Journal of the American Society for Mass Spectrometry (1 paper)PROTEOMICS (1 paper)Combinatorial Chemistry & High Throughput Screening (1 paper)BMC Bioinformatics (1 paper)
- Partner nations
- GermanyIndiaNew Zealand
In The Last Decade
Axel Facius
6 papers receiving 454 citations
Peers
Comparison fields: 5 of 100
- Molecular Biology 343
- Artificial Intelligence 103
- Spectroscopy 49
- Health Information Management 12
- Computer Vision and Pattern Recognition 50
Countries citing papers authored by Axel Facius
This map shows the geographic impact of Axel Facius'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 Axel Facius with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Axel Facius more than expected).
Fields of papers citing papers by Axel Facius
This network shows the impact of papers produced by Axel Facius. 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 Axel Facius. The network helps show where Axel Facius may publish in the future.
Co-authors
The 21 scholars most cited alongside Axel Facius, 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 | 2005 | 287 | |
| 2 | 2003 | 92 | |
| 3 | 2003 | 61 | |
| 4 | 2005 | 32 | |
| 5 | 2005 | 10 | |
| 6 | 2004 | 1 |
About Axel Facius
Axel Facius is a scholar working on Molecular Biology, Spectroscopy, Plant Science, Infectious Diseases and Organic Chemistry, having authored 6 papers that have together received 483 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (4 papers), Genomics and Phylogenetic Studies (3 papers), Advanced Proteomics Techniques and Applications (2 papers), Wheat and Barley Genetics and Pathology (1 paper), Machine Learning in Bioinformatics (1 paper), Microbial Metabolic Engineering and Bioproduction (1 paper), Metabolomics and Mass Spectrometry Studies (1 paper) and Molecular Biology Techniques and Applications (1 paper). The work is most often cited by research in Molecular Biology (343 citations), Artificial Intelligence (103 citations), Spectroscopy (49 citations), Health Information Management (12 citations) and Computer Vision and Pattern Recognition (50 citations). Axel Facius has collaborated with scholars based in Germany, India and New Zealand. Frequent co-authors include Klaus Mayer, Igor V. Tetko, Hans‐Werner Mewes, Eibe Frank, Yu Wang, Mark A. Hall, Andreas Graner, Thomas Thiel, Nils Stein and Stephen Rudd. Their work appears in journals such as Molecular Genetics and Genomics, Journal of the American Society for Mass Spectrometry, PROTEOMICS, Combinatorial Chemistry & High Throughput Screening and BMC 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.