F G Hanisch
- Molecular Biology top 10%
- Immunology top 10%
- Organic Chemistry top 10%
- Radiology, Nuclear Medicine and Imaging top 5%
- Nutrition and Dietetics top 10%
- Co-authors
- Stefan MüllerG. UhlenbruckJasna Peter‐KatalinićHeinz EggeC. HanskiJ. Da̧browskiUrsula DąbrowskiJörg Hacker
- Topics
- Glycosylation and Glycoproteins Research (18 papers)Galectins and Cancer Biology (10 papers)Monoclonal and Polyclonal Antibodies Research (9 papers)
- Partner nations
- GermanyUnited StatesFrance
In The Last Decade
F G Hanisch
23 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 83
- Molecular Biology 870
- Immunology 392
- Organic Chemistry 297
- Radiology, Nuclear Medicine and Imaging 284
- Nutrition and Dietetics 131
Countries citing papers authored by F G Hanisch
This map shows the geographic impact of F G Hanisch'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 F G Hanisch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites F G Hanisch more than expected).
Fields of papers citing papers by F G Hanisch
This network shows the impact of papers produced by F G Hanisch. 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 F G Hanisch. The network helps show where F G Hanisch may publish in the future.
Co-authorship network of co-authors of F G Hanisch
This figure shows the co-authorship network connecting the top 25 collaborators of F G Hanisch. A scholar is included among the top collaborators of F G Hanisch 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 F G Hanisch. F G Hanisch is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 11 | |
| 2 | 18 | |
| 3 | 73 | |
| 4 | 166 | |
| 5 | 27 | |
| 6 | 4 | |
| 7 | 226 | |
| 8 | 52 | |
| 9 | Altered glycosylation of the MUC-1 protein core contributes to the colon carcinoma-associated increase of mucin-bound sialyl-Lewis(x) expression. | 69 |
| 10 | 5 | |
| 11 | Monoclonal antibody SP-21 defines a sialosyl-Tn antigen expressed on carcinomas and K562 erythroleukemia cells. | 8 |
| 12 | 17 | |
| 13 | 13 | |
| 14 | Sialyl Lewis(x) antigen as defined by monoclonal antibody AM-3 is a marker of dysplasia in the colonic adenoma-carcinoma sequence. | 58 |
| 15 | The lectin from the algae Udotea petiolata: isolation, characterization and sugar binding properties. | 1 |
| 16 | 3 | |
| 17 | 32 | |
| 18 | 155 | |
| 19 | 13 | |
| 20 | 8 |
About F G Hanisch
F G Hanisch is a scholar working on Immunology, Radiology, Nuclear Medicine and Imaging and Nutrition and Dietetics, having authored 23 papers that have together received 1.1k indexed citations. Recurring topics across this work include Glycosylation and Glycoproteins Research (18 papers), Galectins and Cancer Biology (10 papers) and Monoclonal and Polyclonal Antibodies Research (9 papers). The work is most often cited by research in Immunology (392 citations), Molecular Biology (870 citations) and Radiology, Nuclear Medicine and Imaging (284 citations). F G Hanisch has collaborated with scholars based in Germany, United States and France. Frequent co-authors include Stefan Müller, G. Uhlenbruck, Jasna Peter‐Katalinić, Heinz Egge, C. Hanski, J. Da̧browski, Ursula Dąbrowski, Jörg Hacker, Horst Schroten and V. Wahn. Their work appears in journals such as Journal of Biological Chemistry, Biochemistry and Biochemical Journal.
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.