F Buijs

1.8k total citations
11 papers, 1.4k citations indexed

About

F Buijs is a scholar working on Molecular Biology, Immunology and Genetics. According to data from OpenAlex, F Buijs has authored 11 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 8 papers in Immunology and 5 papers in Genetics. Recurrent topics in F Buijs's work include Glycosylation and Glycoproteins Research (7 papers), Virus-based gene therapy research (4 papers) and Immunotherapy and Immune Responses (4 papers). F Buijs is often cited by papers focused on Glycosylation and Glycoproteins Research (7 papers), Virus-based gene therapy research (4 papers) and Immunotherapy and Immune Responses (4 papers). F Buijs collaborates with scholars based in Netherlands. F Buijs's co-authors include John Hilkens, Marjolijn J. L. Ligtenberg, Hans L. Vos, Jero Calafat, Ph. Hageman, J. Hilgers, Arnoud Sonnenberg, S. V. Litvinov, Cornelis J.M. Melief and E. van de Wiel-van Kemenade and has published in prestigious journals such as Journal of Biological Chemistry, The Journal of Immunology and JNCI Journal of the National Cancer Institute.

In The Last Decade

F Buijs

11 papers receiving 1.3k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
F Buijs Netherlands 9 1.1k 545 530 284 164 11 1.4k
Nigel Peat United Kingdom 6 1.2k 1.1× 454 0.8× 540 1.0× 273 1.0× 298 1.8× 6 1.4k
Yasuo Fukushi Japan 12 1.0k 1.0× 464 0.9× 453 0.9× 120 0.4× 237 1.4× 20 1.3k
Marco Bestagno Italy 25 800 0.7× 481 0.9× 462 0.9× 552 1.9× 48 0.3× 51 1.9k
Trevor Duhig United Kingdom 14 2.1k 1.9× 932 1.7× 909 1.7× 481 1.7× 509 3.1× 18 2.6k
Bader Siddiki United States 13 1.3k 1.2× 299 0.5× 413 0.8× 338 1.2× 484 3.0× 14 1.6k
Rosalind Graham United Kingdom 18 679 0.6× 258 0.5× 761 1.4× 192 0.7× 134 0.8× 28 1.2k
D. Roelcke Germany 24 766 0.7× 449 0.8× 722 1.4× 63 0.2× 107 0.7× 136 2.2k
T. Tao United States 22 700 0.6× 238 0.4× 342 0.6× 160 0.6× 45 0.3× 45 1.2k
Nicholas F. Landolfi United States 18 792 0.7× 742 1.4× 712 1.3× 234 0.8× 27 0.2× 30 1.6k
Pei‐Xiang Xing Australia 28 1.5k 1.4× 622 1.1× 979 1.8× 556 2.0× 216 1.3× 56 2.4k

Countries citing papers authored by F Buijs

Since Specialization
Citations

This map shows the geographic impact of F Buijs'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 Buijs with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites F Buijs more than expected).

Fields of papers citing papers by F Buijs

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by F Buijs. 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 Buijs. The network helps show where F Buijs may publish in the future.

Co-authorship network of co-authors of F Buijs

This figure shows the co-authorship network connecting the top 25 collaborators of F Buijs. A scholar is included among the top collaborators of F Buijs 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 Buijs. F Buijs is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
1.
Kemenade, E. van de Wiel-van, M J Ligtenberg, Annemiek J. de Boer, et al.. (1993). Episialin (MUC1) inhibits cytotoxic lymphocyte-target cell interaction.. The Journal of Immunology. 151(2). 767–776. 192 indexed citations
2.
Ligtenberg, Marjolijn J. L., F Buijs, Hans L. Vos, & John Hilkens. (1992). Suppression of cellular aggregation by high levels of episialin.. PubMed. 52(8). 2318–24. 283 indexed citations
3.
Ligtenberg, Marjolijn J. L., et al.. (1992). Cell-associated episialin is a complex containing two proteins derived from a common precursor.. Journal of Biological Chemistry. 267(9). 6171–6177. 241 indexed citations
4.
Hilkens, John, F Buijs, & Marjolijn J. L. Ligtenberg. (1989). Complexity of MAM-6, an epithelial sialomucin associated with carcinomas.. PubMed. 49(4). 786–93. 59 indexed citations
5.
Hilkens, John & F Buijs. (1988). Biosynthesis of MAM-6, an epithelial sialomucin. Evidence for involvement of a rare proteolytic cleavage step in the endoplasmic reticulum.. Journal of Biological Chemistry. 263(9). 4215–4222. 117 indexed citations
6.
Hilkens, John, F Buijs, J. Hilgers, et al.. (1984). Monoclonal antibodies against human milk‐fat globule membranes detecting differentiation antigens of the mammary gland and its tumors. International Journal of Cancer. 34(2). 197–206. 404 indexed citations
7.
Hilkens, John, et al.. (1983). Identification of a cellular receptor for mouse mammary tumor virus and mapping of its gene to chromosome 16. Journal of Virology. 45(1). 140–147. 35 indexed citations
8.
Hilkens, John, et al.. (1981). Monoclonal antibodies against human acid α-glucosidase. Biochimica et Biophysica Acta (BBA) - General Subjects. 678(1). 7–11. 33 indexed citations
9.
Calafat, Jero, et al.. (1977). Simultaneous chemical induction of MTV and MLV in vitro. European Journal of Cancer (1965). 13(6). 577–587. 6 indexed citations
10.
Calafat, Jero, et al.. (1977). Biological activities of murine mammary tumour virus in vitro. European Journal of Cancer (1965). 13(6). 539–548. 1 indexed citations
11.
Calafat, Jero, et al.. (1974). Distribution of Virus Particles and Mammary Tumor Virus Antigens in Mouse Mammary Tumors, Transformed BALB/c Mouse Kidney Cells, and GR Ascites Leukemia Cells2. JNCI Journal of the National Cancer Institute. 53(4). 977–991. 29 indexed citations

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.

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