Deepankar Roy

583 citations
7 papers · 482 · h-index 6

Impact in

    • DNA Repair Mechanisms
    • CRISPR and Genetic Engineering
    • Genomics and Chromatin Dynamics
    • DNA and Nucleic Acid Chemistry
    • RNA and protein synthesis mechanisms
    • RNA Research and Splicing
    • T-cell and B-cell Immunology
    • Immune Cell Function and Interaction

Papers in

    • DNA Repair Mechanisms 4
    • DNA and Nucleic Acid Chemistry 3
    • RNA and protein synthesis mechanisms 2
    • RNA Interference and Gene Delivery 1
    • Viral Infectious Diseases and Gene Expression in Insects 1
    • Genomics and Chromatin Dynamics 1
    • T-cell and B-cell Immunology 2

Deepankar Roy

7 papers receiving 476 citations

Peers

Deepankar Roy
Comparison fields: 5 of 36
  • Molecular Biology 416
  • Immunology 82
  • Genetics 61
  • Cancer Research 29
  • Aging 3
Replace Jia Jin with:
Jia Jin China
Annika Pfeiffer Sweden
Francesco M. Piccolo United States
Matthieu Stierlé France
Valentina M. Evdokimova Russia
Bin Xiong China
Juan González‐Vallinas Spain
Nicolas Dénervaud Switzerland
Amber R. Cutter United States
Deepankar Roy relative to Jia Jin China Jia Jin's profile →
Citations per field
00.5×10×20×26×
Jia Jin · 1×
Citations per year

Countries citing papers authored by Deepankar Roy

Since Specialization
Citations

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

Fields of papers citing papers by Deepankar Roy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside Deepankar Roy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Deepankar Roy Line = papers co-authored together Deepankar Roy links everyone, so they are left out of the graph.

All Works

7 of 7 papers shown
#Work
1 2009131
2 2007128
3 2009126
4 200556
5 200625
6 202013
7 20083

About Deepankar Roy

Deepankar Roy is a scholar working on Molecular Biology, Immunology, Oncology, Radiology, Nuclear Medicine and Imaging and Genetics, having authored 7 papers that have together received 482 indexed citations. Recurring topics across this work include DNA Repair Mechanisms (4 papers), DNA and Nucleic Acid Chemistry (3 papers), T-cell and B-cell Immunology (2 papers), RNA and protein synthesis mechanisms (2 papers), RNA Interference and Gene Delivery (1 paper), Viral Infectious Diseases and Gene Expression in Insects (1 paper), Genomics and Chromatin Dynamics (1 paper) and Plant Virus Research Studies (1 paper). The work is most often cited by research in Molecular Biology (416 citations), Immunology (82 citations), Genetics (61 citations), Cancer Research (29 citations) and Aging (3 citations). Deepankar Roy has collaborated with scholars based in United States. Frequent co-authors include Michael R. Lieber, Kefei Yu, Chih‐Lin Hsieh, Zheng Zhang, Zhengfei Lu, Ian S. Haworth, Feng‐Ting Huang, Brad Snedecor, Wendy Sandoval and Salina Louie. Their work appears in journals such as Molecular and Cellular Biology, The FASEB Journal, The Journal of Cell Biology and Methods in enzymology on CD-ROM/Methods in enzymology.

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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