Philip Beesley

2.4k total citations
98 papers, 1.9k citations indexed

About

Philip Beesley is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Cell Biology. According to data from OpenAlex, Philip Beesley has authored 98 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Molecular Biology, 35 papers in Cellular and Molecular Neuroscience and 21 papers in Cell Biology. Recurrent topics in Philip Beesley's work include Neuroscience and Neuropharmacology Research (31 papers), Cellular transport and secretion (17 papers) and Glycosylation and Glycoproteins Research (11 papers). Philip Beesley is often cited by papers focused on Neuroscience and Neuropharmacology Research (31 papers), Cellular transport and secretion (17 papers) and Glycosylation and Glycoproteins Research (11 papers). Philip Beesley collaborates with scholars based in United Kingdom, Canada and Germany. Philip Beesley's co-authors include Eckart D. Gundelfinger, Michael C. Thorndyke, Richard Hawkes, James W. Gurd, Rosemary S. Mummery, Toni Paladino, Karl‐Heinz Smalla, Ruth M. Empson, Kristina Langnaese and Tomas Bollner and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and PLoS ONE.

In The Last Decade

Philip Beesley

91 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Philip Beesley United Kingdom 26 964 835 297 268 181 98 1.9k
Pedro Fernández‐Llebrez Spain 30 839 0.9× 850 1.0× 261 0.9× 303 1.1× 538 3.0× 94 2.8k
Gad D. Vatine Israel 19 711 0.7× 456 0.5× 219 0.7× 237 0.9× 140 0.8× 37 2.1k
Bo Holmqvist Sweden 29 605 0.6× 563 0.7× 345 1.2× 400 1.5× 73 0.4× 63 2.0k
Philippe Vernier France 26 1.1k 1.1× 692 0.8× 362 1.2× 142 0.5× 114 0.6× 55 2.0k
Nicholas Marsh‐Armstrong United States 26 2.0k 2.0× 728 0.9× 260 0.9× 239 0.9× 207 1.1× 40 3.3k
Kohtaro Takei Japan 24 803 0.8× 1.3k 1.6× 524 1.8× 155 0.6× 558 3.1× 80 2.1k
W. Ted Allison Canada 25 1.1k 1.2× 473 0.6× 466 1.6× 98 0.4× 62 0.3× 72 1.7k
Frank Hirth United Kingdom 32 2.1k 2.2× 1.5k 1.8× 373 1.3× 281 1.0× 83 0.5× 63 3.7k
Jesús M. Grondona Spain 21 1.5k 1.6× 480 0.6× 159 0.5× 186 0.7× 347 1.9× 51 2.7k
Yongfu Wang China 24 1.0k 1.1× 310 0.4× 93 0.3× 283 1.1× 43 0.2× 70 1.8k

Countries citing papers authored by Philip Beesley

Since Specialization
Citations

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

Fields of papers citing papers by Philip Beesley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Philip Beesley

This figure shows the co-authorship network connecting the top 25 collaborators of Philip Beesley. A scholar is included among the top collaborators of Philip Beesley 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 Philip Beesley. Philip Beesley 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.
Beesley, Philip, et al.. (2021). Creating space and time for innovation - a methodology for building adaptation design appraisal using physics-based simulation tools and interactive multi-objective optimization. Engineering Construction & Architectural Management. 30(3). 1098–1121. 3 indexed citations
2.
Herrera‐Molina, Rodrigo, Victor Sabanov, Tariq Ahmed, et al.. (2016). Genetically Induced Retrograde Amnesia of Associative Memories After Neuroplastin Ablation. Biological Psychiatry. 81(2). 124–135. 38 indexed citations
3.
Beesley, Philip. (2016). Can architecture embody living systems? Emerging ‘living’ technologies and synthetic biology. Architectural Research Quarterly. 20(2). 92–94. 2 indexed citations
4.
Herrera‐Molina, Rodrigo, Isabella Sarto‐Jackson, Carolina Montenegro‐Venegas, et al.. (2014). Structure of Excitatory Synapses and GABAA Receptor Localization at Inhibitory Synapses Are Regulated by Neuroplastin-65. Journal of Biological Chemistry. 289(13). 8973–8988. 42 indexed citations
5.
Beesley, Philip. (2014). Dissipative Prototyping Methods: A Manifesto. JBIS. 67. 338–345. 1 indexed citations
6.
7.
Beesley, Philip, Mark Burry, Neri Oxman, et al.. (2011). FABRICATE - Making Digital Architecture. UCL Discovery (University College London). 3 indexed citations
8.
Turner, Paul R., et al.. (2009). Molecular interactions of the plasma membrane calcium ATPase 2 at pre- and post-synaptic sites in rat cerebellum. Neuroscience. 162(2). 383–395. 32 indexed citations
9.
Bernstein, Hans‐Gert, Karl‐Heinz Smalla, Bernhard Bogerts, et al.. (2006). The immunolocalization of the synaptic glycoprotein neuroplastin differs substantially between the human and the rodent brain. Brain Research. 1134(1). 107–112. 24 indexed citations
10.
11.
Beesley, Philip, et al.. (1997). JSJ-1, An Anti-Spermidine Monoclonal Antibody With Potential Clinical Applications. Hybridoma. 16(6). 541–543. 1 indexed citations
12.
Langnaese, Kristina, Philip Beesley, & Eckart D. Gundelfinger. (1997). Synaptic Membrane Glycoproteins gp65 and gp55 Are New Members of the Immunoglobulin Superfamily. Journal of Biological Chemistry. 272(2). 821–827. 69 indexed citations
13.
Thorndyke, Michael C., et al.. (1995). Regeneration and post-metamorphic development of the central nervous system in the protochordate Ciona intestinalis: a study with monoclonal antibodies. Cell and Tissue Research. 279(2). 421–432. 37 indexed citations
14.
Bollner, Tomas, Philip Beesley, & Michael C. Thorndyke. (1992). Pattern of substance P‐ and cholecystokinin‐like immunoreactivity during regeneration of the neural complex in the ascidian Ciona intestinalis. The Journal of Comparative Neurology. 325(4). 572–580. 26 indexed citations
15.
Hill, Irene E., et al.. (1992). Molecular Characterisation and Structural Relationship of the Synapse‐Enriched Glycoproteins gp65 and gp55. Journal of Neurochemistry. 58(6). 2037–2043. 18 indexed citations
16.
Beesley, Philip, Toni Paladino, Irene E. Hill, et al.. (1990). Postnatal Development of a Granule Cell‐Enriched, Neurone‐Specific Glycoprotein, gp50, in Normal and Thyroid‐Deficient Rats. Journal of Neurochemistry. 54(2). 505–512. 5 indexed citations
17.
Paladino, Toni, Philip Beesley, Simone M. Nicholson, & James W. Gurd. (1990). Expression of the neuron-specific glycoprotein GP50 by granule cell cultures. Brain Research. 521(1-2). 131–137. 4 indexed citations
18.
Bissoon, Nankie, et al.. (1990). The effect of castanospermine on the synthesis of synaptic glycoproteins by rat brain slices. Neurochemical Research. 15(3). 257–263. 1 indexed citations
19.
Beesley, Philip. (1989). Immunological approaches to the study of synaptic glycoproteins. Comparative Biochemistry and Physiology Part A Physiology. 93(1). 255–266. 12 indexed citations
20.
Paladino, Toni, Philip Beesley, & James W. Gurd. (1987). Molecular characterization of gp50 a neuron specific synaptic enriched glycoprotein. The Society for Neuroscience Abstracts. 13(3). 1711. 1 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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