Gerald Beste

1.3k total citations
9 papers, 989 citations indexed

About

Gerald Beste is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Materials Chemistry. According to data from OpenAlex, Gerald Beste has authored 9 papers receiving a total of 989 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 5 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Materials Chemistry. Recurrent topics in Gerald Beste's work include Monoclonal and Polyclonal Antibodies Research (5 papers), Advanced Biosensing Techniques and Applications (3 papers) and Enzyme Structure and Function (3 papers). Gerald Beste is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (5 papers), Advanced Biosensing Techniques and Applications (3 papers) and Enzyme Structure and Function (3 papers). Gerald Beste collaborates with scholars based in Germany, United States and Japan. Gerald Beste's co-authors include Arne Skerra, Daniel G. Jay, Brenda K. Eustace, Leodevico L. Ilag, Stefan Henning, Blanca Lain, Len Neckers, Jean K. Stewart, Christine Unger and Takashi Sakurai and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Cell Biology and Journal of Molecular Biology.

In The Last Decade

Gerald Beste

9 papers receiving 956 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Gerald Beste Germany	9	790	237	137	132	104	9	989
Thomas R. Hynes United States	15	1.0k 1.3×	151 0.6×	70 0.5×	150 1.1×	173 1.7×	23	1.3k
P. Saludjian France	14	778 1.0×	191 0.8×	86 0.6×	128 1.0×	200 1.9×	22	1000
Glen B. Legge United States	15	661 0.8×	103 0.4×	244 1.8×	118 0.9×	114 1.1×	19	1.0k
Diana Tello France	16	975 1.2×	576 2.4×	273 2.0×	43 0.3×	152 1.5×	24	1.2k
Natalie Thompson Netherlands	15	1.8k 2.3×	154 0.6×	71 0.5×	239 1.8×	133 1.3×	20	2.3k
Christopher C. Valley United States	17	771 1.0×	167 0.7×	185 1.4×	80 0.6×	69 0.7×	20	1.2k
Hiroaki Sasakawa Japan	16	734 0.9×	348 1.5×	169 1.2×	111 0.8×	83 0.8×	23	983
Jens Hennecke Belgium	9	507 0.6×	106 0.4×	281 2.1×	90 0.7×	104 1.0×	11	797
Katie Hardman United States	11	564 0.7×	373 1.6×	154 1.1×	90 0.7×	119 1.1×	14	785
Marc Ribó Spain	21	1.0k 1.3×	70 0.3×	81 0.6×	70 0.5×	263 2.5×	59	1.2k

Countries citing papers authored by Gerald Beste

Since Specialization

Citations

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

Fields of papers citing papers by Gerald Beste

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gerald Beste

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

All Works

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9 of 9 papers shown

Gilbert, Ilka, Susanne Schiffmann, Christian Albrecht, et al.. (2004). Double chip protein arrays using recombinant single‐chain Fv antibody fragments. PROTEOMICS. 4(5). 1417–1420. 12 indexed citations

Eustace, Brenda K., Takashi Sakurai, Jean K. Stewart, et al.. (2004). Functional proteomic screens reveal an essential extracellular role for hsp90α in cancer cell invasiveness. Nature Cell Biology. 6(6). 507–514. 468 indexed citations

Korndörfer, Ingo P., Gerald Beste, & Arne Skerra. (2003). Crystallographic analysis of an “anticalin” with tailored specificity for fluorescein reveals high structural plasticity of the lipocalin loop region. Proteins Structure Function and Bioinformatics. 53(1). 121–129. 39 indexed citations

Beck, Stefan, Takashi Sakurai, Brenda K. Eustace, et al.. (2002). Fluorophore-assisted light inactivation: A high-throughput tool for direct target validation of proteins. PROTEOMICS. 2(3). 247–247. 87 indexed citations

Ilag, Leodevico L., et al.. (2002). Emerging high-throughput drug target validation technologies. Drug Discovery Today. 7(18). S136–S142. 13 indexed citations

Hess, Stephan, et al.. (2002). Ultrafast Electron Transfer in the Complex between Fluorescein and a Cognate Engineered Lipocalin Protein, a So-Called Anticalin. Biochemistry. 41(12). 4156–4164. 38 indexed citations

Schlehuber, S., Gerald Beste, & Arne Skerra. (2000). A novel type of receptor protein, based on the lipocalin scaffold, with specificity for digoxigenin11Edited by R. Huber. Journal of Molecular Biology. 297(5). 1105–1120. 83 indexed citations

Beste, Gerald, et al.. (1999). Small antibody-like proteins with prescribed ligand specificities derived from the lipocalin fold. Proceedings of the National Academy of Sciences. 96(5). 1898–1903. 187 indexed citations

Wiesmann, Christian, Gerald Beste, Wolfgang Hengstenberg, & Georg E. Schulz. (1995). The three-dimensional structure of 6-phospho-β-galactosidase from Lactococcus lactis. Structure. 3(9). 961–968. 62 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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