Falk Schreiber
- Molecular Biology top 10%
- Plant Science top 10%
- Statistical and Nonlinear Physics top 5%
- Biomedical Engineering
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Dirk KoschützkiHenning SchwöbbermeyerEva Grafahrend‐BelauBjörn H. JunkerChristian KlukasHardy RolletschekLjudmilla BorisjukTim Dwyer
- Topics
- Microbial Metabolic Engineering and Bioproduction (15 papers)Bioinformatics and Genomic Networks (14 papers)Gene Regulatory Network Analysis (13 papers)
- Partner nations
- GermanyUnited StatesAustralia
In The Last Decade
Falk Schreiber
32 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 126
- Molecular Biology 725
- Plant Science 249
- Statistical and Nonlinear Physics 133
- Biomedical Engineering 120
- Computer Vision and Pattern Recognition 112
Countries citing papers authored by Falk Schreiber
This map shows the geographic impact of Falk Schreiber'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 Falk Schreiber with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Falk Schreiber more than expected).
Fields of papers citing papers by Falk Schreiber
This network shows the impact of papers produced by Falk Schreiber. 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 Falk Schreiber. The network helps show where Falk Schreiber may publish in the future.
Co-authorship network of co-authors of Falk Schreiber
This figure shows the co-authorship network connecting the top 25 collaborators of Falk Schreiber. A scholar is included among the top collaborators of Falk Schreiber based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Falk Schreiber. Falk Schreiber is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 5 | |
| 3 | 29 | |
| 4 | 0 | |
| 5 | 5 | |
| 6 | 61 | |
| 7 | 61 | |
| 8 | 4 | |
| 9 | 3 | |
| 10 | 22 | |
| 11 | 41 | |
| 12 | 242 | |
| 13 | 55 | |
| 14 | 39 | |
| 15 | 129 | |
| 16 | 35 | |
| 17 | 12 | |
| 18 | 148 | |
| 19 | Representing experimental biological data in metabolic networks | 10 |
| 20 | 1 |
About Falk Schreiber
Falk Schreiber is a scholar working on Information Systems and Management, Molecular Biology and Statistical and Nonlinear Physics, having authored 34 papers that have together received 1.1k indexed citations. Recurring topics across this work include Microbial Metabolic Engineering and Bioproduction (15 papers), Bioinformatics and Genomic Networks (14 papers) and Gene Regulatory Network Analysis (13 papers). The work is most often cited by research in Statistical and Nonlinear Physics (133 citations), Molecular Biology (725 citations) and Biochemistry (62 citations). Falk Schreiber has collaborated with scholars based in Germany, United States and Australia. Frequent co-authors include Dirk Koschützki, Henning Schwöbbermeyer, Eva Grafahrend‐Belau, Björn H. Junker, Christian Klukas, Hardy Rolletschek, Ljudmilla Borisjuk, Tim Dwyer, Ulrich Wobus and Anja Hartmann. Their work appears in journals such as Nucleic Acids Research, Bioinformatics and The Plant Cell.
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.