Chakit Arora
Impact in
- Microbiology top 10%
- Antimicrobial Peptides and Activities
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- Food Allergy and Anaphylaxis Research
Papers in
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- Machine Learning in Bioinformatics 3
- RNA and protein synthesis mechanisms 2
- S100 Proteins and Annexins 1
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- interferon and immune responses 2
- Biomarkers in Disease Mechanisms 1
- Co-authors
- Gajendra P. S. Raghava (12 shared papers)Sumeet Patiyal (5 shared papers)Anjali Dhall (4 shared papers)Neelam Sharma (3 shared papers)Akshara Pande (2 shared papers)Dilraj Kaur (8 shared papers)Purbarun Dhar (1 shared paper)Harpreet Kaur (3 shared papers)
- Journals
- Frontiers in Immunology (2 papers)PLoS ONE (2 papers)Briefings in Bioinformatics (1 paper)Molecular Diagnosis & Therapy (1 paper)Journal of Computational Biology (1 paper)
- Partner nations
- IndiaItalyUnited States
In The Last Decade
Chakit Arora
15 papers receiving 433 citations
Chakit Arora's Hit Papers
Peers
Comparison fields: 5 of 76
- Microbiology 41
- Immunology and Allergy 32
- Molecular Biology 313
- Immunology 77
- Biotechnology 25
Countries citing papers authored by Chakit Arora
This map shows the geographic impact of Chakit Arora'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 Chakit Arora with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chakit Arora more than expected).
Fields of papers citing papers by Chakit Arora
This network shows the impact of papers produced by Chakit Arora. 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 Chakit Arora. The network helps show where Chakit Arora may publish in the future.
Co-authors
The 25 scholars most cited alongside Chakit Arora, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | AlgPred 2.0: an improved method for predicting allergenic proteins and mapping of IgE epitopes Hit paper breakdown → | 2020 | 223 |
| 2 | 2022 | 50 | |
| 3 | 2020 | 27 | |
| 4 | 1976 | 24 | |
| 5 | 2020 | 23 | |
| 6 | 2020 | 16 | |
| 7 | 2019 | 13 | |
| 8 | 2021 | 12 | |
| 9 | 2021 | 11 | |
| 10 | 2024 | 10 | |
| 11 | 2020 | 10 | |
| 12 | 2020 | 9 | |
| 13 | 2021 | 7 | |
| 14 | 2021 | 5 | |
| 15 | 2023 | 1 |
About Chakit Arora
Chakit Arora is a scholar working on Molecular Biology, Immunology, Oncology, Infectious Diseases and Computational Mechanics, having authored 15 papers that have together received 441 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (3 papers), Cutaneous Melanoma Detection and Management (2 papers), interferon and immune responses (2 papers), RNA and protein synthesis mechanisms (2 papers), Heat Transfer and Optimization (1 paper), Biomarkers in Disease Mechanisms (1 paper), Allergic Rhinitis and Sensitization (1 paper) and S100 Proteins and Annexins (1 paper). The work is most often cited by research in Microbiology (41 citations), Immunology and Allergy (32 citations), Molecular Biology (313 citations), Immunology (77 citations) and Biotechnology (25 citations). Chakit Arora has collaborated with scholars based in India, Italy and United States. Frequent co-authors include Gajendra P. S. Raghava, Sumeet Patiyal, Anjali Dhall, Neelam Sharma, Akshara Pande, Dilraj Kaur, Purbarun Dhar, Harpreet Kaur, Piyush Agrawal and Rajesh Kumar. Their work appears in journals such as Frontiers in Immunology, PLoS ONE, Briefings in Bioinformatics, Molecular Diagnosis & Therapy and Journal of Computational Biology.
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.