Deepak Raina

412 citations
16 papers · 293 · h-index 6

Impact in

    • Chronic Myeloid Leukemia Treatments
    • Glycosylation and Glycoproteins Research
    • Protein Kinase Regulation and GTPase Signaling
    • Cell death mechanisms and regulation
    • Mitochondrial Function and Pathology

Papers in

Deepak Raina

15 papers receiving 285 citations

Peers

Deepak Raina
Comparison fields: 5 of 66
  • Hematology 66
  • Molecular Biology 175
  • Cell Biology 31
  • Immunology 38
  • Oncology 48
Replace Shang Su with:
Shang Su China
Pavithra Shyamsunder Singapore
Chunjie Yu China
Frank J. McMahon United States
Sumiko Takao Japan
Ruikai Du China
Nicole Kreuzberg Germany
Bing Long China
Juying Zhou China
Deepak Raina relative to Shang Su China Shang Su's profile →
Citations per field
00.5×
Shang Su · 1×
Citations per year

Countries citing papers authored by Deepak Raina

Since Specialization
Citations

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

Fields of papers citing papers by Deepak Raina

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Deepak Raina, 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 Deepak Raina Line = papers co-authored together Deepak Raina links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 200197
2 200674
3 200345
4 202123
5 200219
6 202111
7 20225
8 20235
9 20243
10 20243
11 20173
12 20192
13 20251
14 20211
15 20021
16 20260

About Deepak Raina

Deepak Raina is a scholar working on Hematology, Ecology, Evolution, Behavior and Systematics, Biomedical Engineering, Surgery and Aerospace Engineering, having authored 16 papers that have together received 293 indexed citations. Recurring topics across this work include Chronic Myeloid Leukemia Treatments (5 papers), Fungal Plant Pathogen Control (4 papers), Surgical Simulation and Training (3 papers), Quinazolinone synthesis and applications (2 papers), Chronic Lymphocytic Leukemia Research (2 papers), Advanced X-ray and CT Imaging (2 papers), Soft Robotics and Applications (2 papers) and Ultrasound in Clinical Applications (2 papers). The work is most often cited by research in Hematology (66 citations), Molecular Biology (175 citations), Cell Biology (31 citations), Immunology (38 citations) and Oncology (48 citations). Deepak Raina has collaborated with scholars based in India, United States and United Kingdom. Frequent co-authors include Donald Küfe, Shailendra Kumar, Surender Kharbanda, Satya Saxena, Neerad C. Mishra, Ajit Bharti, Rehan Ahmad, Jian Ren, Kiyotsugu Yoshida and Suril V. Shah. Their work appears in journals such as Molecular Pharmacology, Acta Astronautica, The EMBO Journal, IEEE Transactions on Medical Robotics and Bionics and Journal of Biological Chemistry.

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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