Gurdip Hansra

930 total citations
8 papers, 767 citations indexed

About

Gurdip Hansra is a scholar working on Molecular Biology, Cell Biology and Physiology. According to data from OpenAlex, Gurdip Hansra has authored 8 papers receiving a total of 767 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 3 papers in Cell Biology and 1 paper in Physiology. Recurrent topics in Gurdip Hansra's work include Protein Kinase Regulation and GTPase Signaling (5 papers), Cellular transport and secretion (3 papers) and T-cell and B-cell Immunology (1 paper). Gurdip Hansra is often cited by papers focused on Protein Kinase Regulation and GTPase Signaling (5 papers), Cellular transport and secretion (3 papers) and T-cell and B-cell Immunology (1 paper). Gurdip Hansra collaborates with scholars based in United Kingdom, Australia and Switzerland. Gurdip Hansra's co-authors include Peter J. Parker, Frédéric Bornancin, Corinne Prévostel, Richard D. H. Whelan, Phillip J. Robinson, Mark E. Graham, Sandra Schmidt, Anthony Squire, William H. Harris and Diana M. Barnes and has published in prestigious journals such as Science, Journal of Biological Chemistry and Nature Cell Biology.

In The Last Decade

Gurdip Hansra

8 papers receiving 755 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Gurdip Hansra United Kingdom	7	588	264	129	102	69	8	767
Jeffrey Klarenbeek Netherlands	13	649 1.1×	139 0.5×	143 1.1×	86 0.8×	37 0.5×	18	874
Alex Berndt United Kingdom	10	761 1.3×	128 0.5×	226 1.8×	48 0.5×	84 1.2×	12	1.2k
Joseph S. Soughayer United States	9	827 1.4×	99 0.4×	134 1.0×	39 0.4×	49 0.7×	9	1.1k
Yihong Yao United States	13	724 1.2×	138 0.5×	255 2.0×	31 0.3×	104 1.5×	18	969
Anka G Ehrhardt United States	10	443 0.8×	132 0.5×	91 0.7×	83 0.8×	82 1.2×	10	584
Ying J. Buechler United States	7	649 1.1×	94 0.4×	130 1.0×	116 1.1×	36 0.5×	8	830
Kenneth Takeda France	17	660 1.1×	282 1.1×	324 2.5×	23 0.2×	76 1.1×	30	1.1k
Jane Dingus United States	17	793 1.3×	352 1.3×	261 2.0×	22 0.2×	40 0.6×	25	1.1k
Valentina Lissandron Italy	18	1.3k 2.1×	172 0.7×	248 1.9×	66 0.6×	76 1.1×	20	1.5k
Chika Ohshima Japan	7	507 0.9×	141 0.5×	61 0.5×	93 0.9×	58 0.8×	8	681

Countries citing papers authored by Gurdip Hansra

Since Specialization

Citations

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

Fields of papers citing papers by Gurdip Hansra

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gurdip Hansra

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

All Works

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8 of 8 papers shown

Antonenas, Vicki, et al.. (2015). G-CSF primed donor haematopoietic stem cell collections are associated with reduced viable T cell yield for donor lymphocyte infusion. Cytotherapy. 17(6). S57–S57. 1 indexed citations

Hansra, Gurdip, et al.. (2010). Differential Phosphorylation of Dynamin I Isoforms in Subcellular Compartments Demonstrates the Hidden Complexity of Phosphoproteomes. Journal of Proteome Research. 9(8). 4028–4037. 18 indexed citations

Tan, Timothy C., Valentina A. Valova, Chandra S. Malladi, et al.. (2003). Cdk5 is essential for synaptic vesicle endocytosis. Nature Cell Biology. 5(8). 701–710. 243 indexed citations

Hansra, Gurdip, et al.. (1999). Multisite dephosphorylation and desensitization of conventional protein kinase C isotypes. Biochemical Journal. 342(2). 337–344. 117 indexed citations

Ng, Tony, Anthony Squire, Gurdip Hansra, et al.. (1999). Imaging Protein Kinase Cα Activation in Cells. Science. 283(5410). 2085–2089. 234 indexed citations

Hansra, Gurdip, Frédéric Bornancin, Richard D. H. Whelan, Brian A. Hemmings, & Peter J. Parker. (1996). 12-O-Tetradecanoylphorbol-13-acetate-induced Dephosphorylation of Protein Kinase Cα Correlates with the Presence of a Membrane-associated Protein Phosphatase 2A Heterotrimer. Journal of Biological Chemistry. 271(51). 32785–32788. 92 indexed citations

Olivier, Andrée R., Gurdip Hansra, Trevor R. Pettitt, Michael J.O. Wakelam, & Peter J. Parker. (1996). The co-mitogenic combination of transforming growth factor β1 and bombesin protects protein kinase C-δ from late-phase down-regulation, despite synergy in diacylglycerol accumulation. Biochemical Journal. 318(2). 519–525. 16 indexed citations

Parker, Peter J., Lisardo Boscá, Lodewijk V. Dekker, et al.. (1995). Protein kinase C (PKC)-induced PKC degradation: a model for down-regulation. Biochemical Society Transactions. 23(1). 153–155. 46 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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