Subhojit Roy

6.4k total citations · 1 hit paper
65 papers, 4.2k citations indexed

About

Subhojit Roy is a scholar working on Cell Biology, Molecular Biology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Subhojit Roy has authored 65 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Cell Biology, 23 papers in Molecular Biology and 20 papers in Cellular and Molecular Neuroscience. Recurrent topics in Subhojit Roy's work include Parkinson's Disease Mechanisms and Treatments (15 papers), Microtubule and mitosis dynamics (13 papers) and Cellular transport and secretion (13 papers). Subhojit Roy is often cited by papers focused on Parkinson's Disease Mechanisms and Treatments (15 papers), Microtubule and mitosis dynamics (13 papers) and Cellular transport and secretion (13 papers). Subhojit Roy collaborates with scholars based in United States, France and Israel. Subhojit Roy's co-authors include Utpal Das, David Scott, John Q. Trojanowski, Jichao Sun, Virginia M.‐Y. Lee, Archan Ganguly, Eliezer Masliah, Bin Zhang, Yong Tang and Lina Wang and has published in prestigious journals such as New England Journal of Medicine, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Subhojit Roy

62 papers receiving 4.2k citations

Hit Papers

Patches of Disorganization in the Neocortex of Children w... 2014 2026 2018 2022 2014 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Subhojit Roy United States 31 1.5k 1.3k 1.3k 1.2k 1.2k 65 4.2k
Dick Jaarsma Netherlands 39 2.2k 1.5× 1.6k 1.2× 1.3k 1.1× 613 0.5× 911 0.8× 76 4.7k
Manu Sharma United States 25 2.0k 1.4× 1.5k 1.1× 2.5k 2.0× 1.6k 1.3× 1.4k 1.2× 36 5.5k
Kirsten Harvey United Kingdom 37 3.1k 2.1× 2.6k 2.0× 1.8k 1.5× 1.0k 0.8× 1.2k 1.0× 64 5.6k
John F. Crary United States 31 1.7k 1.2× 1.1k 0.8× 1.1k 0.9× 1.2k 1.0× 336 0.3× 111 4.1k
Marc Flajolet United States 33 2.4k 1.6× 2.0k 1.5× 633 0.5× 797 0.7× 433 0.4× 65 4.8k
Markus Morawski Germany 35 1.5k 1.0× 1.2k 0.9× 307 0.2× 778 0.6× 1.3k 1.1× 108 4.1k
Myriam Heiman United States 26 2.7k 1.9× 1.7k 1.3× 713 0.6× 736 0.6× 654 0.5× 36 5.4k
Howard D. Rees United States 30 2.2k 1.5× 1.6k 1.2× 870 0.7× 1.2k 1.0× 511 0.4× 61 4.4k
Paul T. Kotzbauer United States 31 2.1k 1.5× 1.6k 1.2× 2.1k 1.7× 1.8k 1.5× 472 0.4× 52 5.2k
Ji Won Um South Korea 29 1.8k 1.3× 1.4k 1.0× 399 0.3× 1.1k 0.9× 569 0.5× 65 3.2k

Countries citing papers authored by Subhojit Roy

Since Specialization
Citations

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

Fields of papers citing papers by Subhojit Roy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Subhojit Roy

This figure shows the co-authorship network connecting the top 25 collaborators of Subhojit Roy. A scholar is included among the top collaborators of Subhojit Roy 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 Subhojit Roy. Subhojit Roy 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.
Boyer, Nicholas P., Theresa Wiesner, Nicolas Jullien, et al.. (2025). Spectrin condensates provide a nidus for assembling the axonal membrane-associated periodic skeleton. iScience. 29(1). 114454–114454.
2.
Parra‐Rivas, Leonardo A, et al.. (2023). In vivo safety and efficacy of a CRISPR‐based gene therapy for Alzheimer’s disease. Alzheimer s & Dementia. 19(S21).
3.
Parra‐Rivas, Leonardo A, et al.. (2023). Synapsin E-domain is essential for α-synuclein function. eLife. 12. 4 indexed citations
4.
Parra‐Rivas, Leonardo A, Kayalvizhi Madhivanan, Lina Wang, et al.. (2023). Serine-129 phosphorylation of α-synuclein is an activity-dependent trigger for physiologic protein-protein interactions and synaptic function. Neuron. 111(24). 4006–4023.e10. 62 indexed citations
5.
Ganguly, Archan & Subhojit Roy. (2022). Imaging Diversity in Slow Axonal Transport. Methods in molecular biology. 2431. 163–179. 3 indexed citations
6.
Wang, Yuyuan, Kathy J. Snow, Stephen A. Murray, et al.. (2022). Efficient in vivo neuronal genome editing in the mouse brain using nanocapsules containing CRISPR-Cas9 ribonucleoproteins. Biomaterials. 293. 121959–121959. 19 indexed citations
7.
Sun, Jichao & Subhojit Roy. (2021). Gene-based therapies for neurodegenerative diseases. Nature Neuroscience. 24(3). 297–311. 116 indexed citations
8.
Sun, Jichao, Jared Carlson-Stevermer, Utpal Das, et al.. (2018). CRISPR/Cas9 editing of APP C-terminus attenuates β-cleavage and promotes α-cleavage. Nature Communications. 10(1). 53–53. 79 indexed citations
9.
Roy, Subhojit, et al.. (2018). Actin Assemblies in the Axon Shaft – some Open Questions. Current Opinion in Neurobiology. 51. 163–167. 11 indexed citations
10.
Palmeri, Agostino, Roberta Ricciarelli, Walter Gulisano, et al.. (2017). Amyloid-β Peptide Is Needed for cGMP-Induced Long-Term Potentiation and Memory. Journal of Neuroscience. 37(29). 6926–6937. 62 indexed citations
11.
Ganguly, Archan, Yong Tang, Lina Wang, et al.. (2015). A dynamic formin-dependent deep F-actin network in axons. The Journal of Cell Biology. 210(3). 401–417. 131 indexed citations
12.
Das, Utpal, Lina Wang, Archan Ganguly, et al.. (2015). Visualizing APP and BACE-1 approximation in neurons yields insight into the amyloidogenic pathway. Nature Neuroscience. 19(1). 55–64. 146 indexed citations
13.
Chow, Maggie, Maureen P. Boyle, Susan M. Sunkin, et al.. (2014). Patches of Disorganization in the Neocortex of Children with Autism. New England Journal of Medicine. 370(13). 1209–1219. 507 indexed citations breakdown →
14.
Wang, Lina, Utpal Das, David Scott, et al.. (2014). α-Synuclein Multimers Cluster Synaptic Vesicles and Attenuate Recycling. Current Biology. 24(19). 2319–2326. 205 indexed citations
15.
Das, Utpal, et al.. (2013). Activity-Induced Convergence of APP and BACE-1 in Acidic Microdomains via an Endocytosis-Dependent Pathway. Neuron. 79(3). 447–460. 175 indexed citations
16.
Scott, David, Utpal Das, Yong Tang, & Subhojit Roy. (2011). Mechanistic Logic Underlying the Axonal Transport of Cytosolic Proteins. Neuron. 70(3). 441–454. 83 indexed citations
17.
Roy, Subhojit, et al.. (2011). A simple photoactivation and image analysis module for visualizing and analyzing axonal transport with high temporal resolution. Nature Protocols. 7(1). 62–68. 21 indexed citations
18.
Roy, Subhojit, Matthew J. Winton, Mark M. Black, John Q. Trojanowski, & Virginia M.‐Y. Lee. (2008). Cytoskeletal Requirements in Axonal Transport of Slow Component-b. Journal of Neuroscience. 28(20). 5248–5256. 40 indexed citations
19.
Roy, Subhojit, Matthew J. Winton, Mark M. Black, John Q. Trojanowski, & Virginia M.‐Y. Lee. (2007). Rapid and Intermittent Cotransport of Slow Component-b Proteins. Journal of Neuroscience. 27(12). 3131–3138. 77 indexed citations
20.
Francis, Paul S., Subhojit Roy, Scott T. Brady, & Mark M. Black. (2005). Transport of neurofilaments in growing axons requires microtubules but not actin filaments. Journal of Neuroscience Research. 79(4). 442–450. 36 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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