Manoj Bhasin

11.3k citations
164 papers · 7.8k indexed · 3 hit papers · h-index 47

Impact in

    • vaccines and immunoinformatics approaches
    • Machine Learning in Bioinformatics
    • RNA and protein synthesis mechanisms
    • Genomics and Phylogenetic Studies
    • Epigenetics and DNA Methylation
  • Immunology top 2%
    • Immunotherapy and Immune Responses

Papers in

Manoj Bhasin

158 papers receiving 7.6k citations

Hit Papers

Single cell transcriptomic landscape of diabetic foot ulcers 2022 · 251 citations
2512011202620162021100200300400

Peers

Manoj Bhasin
Comparison fields: 5 of 170
  • Molecular Biology 4.7k
  • Immunology 1.3k
  • Nephrology 410
  • Cancer Research 866
  • Transplantation 136
Replace Wenzhong Xiao with:
Wenzhong Xiao United States
Thomas M. Stulnig Austria
Kazuo Takahashi Japan
Carl J. Hauser United States
R. William G. Watson Ireland
Gregory P. Downey Canada
Assam El‐Osta Australia
Hui Zhang China
Huey‐Kang Sytwu Taiwan
Daniel R. Goldstein United States
Manoj Bhasin relative to Wenzhong Xiao United States Wenzhong Xiao's profile →
Citations per field
00.5×4.7×
Wenzhong Xiao · 1×
Citations per year

Countries citing papers authored by Manoj Bhasin

Since Specialization
Citations

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

Fields of papers citing papers by Manoj Bhasin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20245
3 20241
4 202410
5 20238
6 20234
7 202338
8 201838
9 201846
10 201817
11 201736
12 201628
13 201567
14 20146
15 201449
16 20142
17 2009142
18 2008134
19 200779
20 200328

About Manoj Bhasin

Manoj Bhasin is a scholar working on Hematology, Biological Psychiatry, Cancer Research, Immunology and Behavioral Neuroscience, having authored 164 papers that have together received 7.8k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (16 papers), Single-cell and spatial transcriptomics (12 papers), vaccines and immunoinformatics approaches (12 papers), Acute Myeloid Leukemia Research (11 papers), Machine Learning in Bioinformatics (10 papers), Immunotherapy and Immune Responses (10 papers), Renal cell carcinoma treatment (8 papers) and T-cell and B-cell Immunology (8 papers). The work is most often cited by research in Molecular Biology (4.7k citations), Immunology (1.3k citations), Nephrology (410 citations), Cancer Research (866 citations) and Transplantation (136 citations). Manoj Bhasin has collaborated with scholars based in United States, India and Germany. Frequent co-authors include Gajendra P. S. Raghava, Towia A. Libermann, S. Ananth Karumanchi, Ankit Garg, Isaac E. Stillman, Zsuzsanna K. Zsengellér, Aarti Garg, Samir M. Parikh, Mei Tran and Eliyahu V. Khankin. Their work appears in journals such as Blood, PLoS ONE, Cancer Research, Scientific Reports and Nucleic Acids Research.

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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