Allan C. Shaw

1.2k total citations
28 papers, 856 citations indexed

About

Allan C. Shaw is a scholar working on Molecular Biology, Epidemiology and Microbiology. According to data from OpenAlex, Allan C. Shaw has authored 28 papers receiving a total of 856 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 8 papers in Epidemiology and 7 papers in Microbiology. Recurrent topics in Allan C. Shaw's work include Reproductive tract infections research (7 papers), Urinary Tract Infections Management (6 papers) and Gut microbiota and health (3 papers). Allan C. Shaw is often cited by papers focused on Reproductive tract infections research (7 papers), Urinary Tract Infections Management (6 papers) and Gut microbiota and health (3 papers). Allan C. Shaw collaborates with scholars based in Denmark, United States and United Kingdom. Allan C. Shaw's co-authors include Lauge Schäffer, Svend Birkelund, Gunna Christiansen, Rita Slaaby, Peter Roepstorff, Martin R. Larsen, Asser S. Andersen, Ida Stenfeldt Mathiasen, Jakob Brandt and Inger Lautrup-Larsen and has published in prestigious journals such as Journal of Biological Chemistry, Molecular and Cellular Biology and Brain.

In The Last Decade

Allan C. Shaw

28 papers receiving 847 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Allan C. Shaw Denmark 16 467 179 149 133 131 28 856
Essam Refai Sweden 15 325 0.7× 172 1.0× 150 1.0× 200 1.5× 90 0.7× 17 697
Fabio Talamo Italy 19 801 1.7× 74 0.4× 27 0.2× 140 1.1× 82 0.6× 28 1.2k
Daisuke Irikura Japan 16 420 0.9× 28 0.2× 54 0.4× 68 0.5× 101 0.8× 29 946
Zhenqi Zhou United States 17 536 1.1× 48 0.3× 65 0.4× 78 0.6× 161 1.2× 35 1.0k
Stephen Sande United States 8 371 0.8× 274 1.5× 51 0.3× 33 0.2× 211 1.6× 9 935
Kathryn A. Skelding Australia 19 679 1.5× 125 0.7× 18 0.1× 49 0.4× 113 0.9× 34 1.2k
Liana Verinaud Brazil 21 311 0.7× 60 0.3× 26 0.2× 30 0.2× 188 1.4× 61 1.1k
Ana Paula Lepique Brazil 21 459 1.0× 29 0.2× 60 0.4× 90 0.7× 311 2.4× 40 1.3k
Huamei Forsman Sweden 26 1.3k 2.8× 191 1.1× 49 0.3× 69 0.5× 114 0.9× 90 1.9k
Michele Fuortes United States 13 366 0.8× 50 0.3× 13 0.1× 127 1.0× 119 0.9× 16 1.0k

Countries citing papers authored by Allan C. Shaw

Since Specialization
Citations

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

Fields of papers citing papers by Allan C. Shaw

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Allan C. Shaw. 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 Allan C. Shaw. The network helps show where Allan C. Shaw may publish in the future.

Co-authorship network of co-authors of Allan C. Shaw

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

All Works

20 of 20 papers shown
1.
Shaw, Allan C., Cleide Dos Santos Souza, Yolanda de Diego‐Otero, et al.. (2024). C9ORF72 patient-derived endothelial cells drive blood-brain barrier disruption and contribute to neurotoxicity. Fluids and Barriers of the CNS. 21(1). 34–34. 4 indexed citations
2.
Bell, Simon, Katy Barnes, Allan C. Shaw, et al.. (2024). Increasing hexokinase 1 expression improves mitochondrial and glycolytic functional deficits seen in sporadic Alzheimer’s disease astrocytes. Molecular Psychiatry. 30(4). 1369–1382. 7 indexed citations
3.
Bauer, Claudia S., Christopher P Webster, Allan C. Shaw, et al.. (2022). Loss of TMEM106B exacerbates C9ALS/FTD DPR pathology by disrupting autophagosome maturation. Frontiers in Cellular Neuroscience. 16. 1061559–1061559. 9 indexed citations
4.
Vernet, Erik, et al.. (2020). Engineering Xaa-Pro dipeptidyl aminopeptidase for specific cleavage of glucagon and glucagon-like peptide 1 from fusion proteins. Protein Expression and Purification. 170. 105590–105590. 1 indexed citations
5.
Johansson, Eva, Jakob Lerche Hansen, Ann Maria Kruse Hansen, et al.. (2016). Type II Turn of Receptor-bound Salmon Calcitonin Revealed by X-ray Crystallography. Journal of Biological Chemistry. 291(26). 13689–13698. 35 indexed citations
6.
7.
Andersen, Asser S., Eva Palmqvist, Allan C. Shaw, et al.. (2010). Backbone cyclic insulin. Journal of Peptide Science. 16(9). 473–479. 12 indexed citations
8.
Birkelund, Svend, et al.. (2009). Analysis of proteins inChlamydia trachomatisL2 outer membrane complex, COMC. FEMS Immunology & Medical Microbiology. 55(2). 187–195. 17 indexed citations
9.
Schäffer, Lauge, Christian L. Brand, Ulla Ribel, et al.. (2008). A novel high-affinity peptide antagonist to the insulin receptor. Biochemical and Biophysical Research Communications. 376(2). 380–383. 130 indexed citations
10.
Slaaby, Rita, Lauge Schäffer, Inger Lautrup-Larsen, et al.. (2006). Hybrid Receptors Formed by Insulin Receptor (IR) and Insulin-like Growth Factor I Receptor (IGF-IR) Have Low Insulin and High IGF-1 Affinity Irrespective of the IR Splice Variant. Journal of Biological Chemistry. 281(36). 25869–25874. 157 indexed citations
11.
Luo, Yuanming, Jindan Zhang, Yanxin Liu, et al.. (2005). Comparative Proteome Analysis of Breast Cancer and Normal Breast. Molecular Biotechnology. 29(3). 233–244. 19 indexed citations
12.
Shaw, Allan C., Martin R. Larsen, Peter Roepstorff, Gunna Christiansen, & Svend Birkelund. (2002). Identification and characterization of a novelChlamydia trachomatisreticulate body protein. FEMS Microbiology Letters. 212(2). 193–202. 5 indexed citations
13.
Shaw, Allan C., Gunna Christiansen, Peter Roepstorff, & Svend Birkelund. (2000). Genetic differences in the tryptophan synthase α-subunit can explain variations in serovar pathogenesis. Microbes and Infection. 2(6). 581–592. 36 indexed citations
14.
15.
Scanlon, Mary, et al.. (1999). Modifications of the cytoskeleton in Encephalitozoon-infected cells.. PubMed. 46(5). 36S–37S. 4 indexed citations
16.
17.
Shaw, Allan C., Gunna Christiansen, & Svend Birkelund. (1999). Effects of interferon gamma onChlamydia trachomatis serovar A and L2 protein expression investigated by two-dimensional gel electrophoresis. Electrophoresis. 20(4-5). 775–780. 15 indexed citations
18.
Shaw, Allan C., Martin R. Larsen, Peter Roepstorff, et al.. (1999). Mapping and identification of interferon gamma-regulated HeLa cell proteins separated by immobilized pH gradient two-dimensional gel electrophoresis. Electrophoresis. 20(4-5). 984–993. 45 indexed citations
19.
Teodorescu, Marius, et al.. (1991). Covalent disulfide binding of human IL-1β to α2-macroglobulin: Inhibition by d-penicillamine. Molecular Immunology. 28(4-5). 323–331. 10 indexed citations
20.
Schleuning, Wolf‐Dieter, et al.. (1987). Plasminogen Activator Inhibitor 2: Regulation of Gene Transcription during Phorbol Ester-Mediated Differentiation of U-937 Human Histiocytic Lymphoma Cells. Molecular and Cellular Biology. 7(12). 4564–4567. 23 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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