Abel Chandra
Impact in
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- Machine Learning in Bioinformatics
- RNA and protein synthesis mechanisms
- Genomics and Phylogenetic Studies
- Protein Structure and Dynamics
- vaccines and immunoinformatics approaches
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- Computational Drug Discovery Methods
Papers in
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- Machine Learning in Bioinformatics 8
- RNA and protein synthesis mechanisms 4
- Genomics and Phylogenetic Studies 4
- Protein Structure and Dynamics 3
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- IoT and Edge/Fog Computing 3
- Energy Efficient Wireless Sensor Networks 1
- Internet of Things and Social Network Interactions 1
- Co-authors
- Regina Grätz (1 shared paper)Tommy Löfstedt (1 shared paper)Abdollah Dehzangi (7 shared papers)Alok Sharma (7 shared papers)Tatsuhiko Tsunoda (7 shared papers)Seong Ro Lee (4 shared papers)Daichi Shigemizu (2 shared papers)Sang Hyeok Park (1 shared paper)
- Journals
- Scientific Reports (2 papers)BMC Genomics (1 paper)BMC Bioinformatics (1 paper)eLife (1 paper)Genes (1 paper)
- Partner nations
- FijiJapanUnited States
In The Last Decade
Abel Chandra
15 papers receiving 262 citations
Peers
Comparison fields: 5 of 73
- Molecular Biology 184
- Computational Theory and Mathematics 34
- Clinical Biochemistry 12
- Microbiology 10
- Health Informatics 2
Countries citing papers authored by Abel Chandra
This map shows the geographic impact of Abel Chandra'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 Abel Chandra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Abel Chandra more than expected).
Fields of papers citing papers by Abel Chandra
This network shows the impact of papers produced by Abel Chandra. 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 Abel Chandra. The network helps show where Abel Chandra may publish in the future.
Co-authors
The 18 scholars most cited alongside Abel Chandra, 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 | 2023 | 96 | |
| 2 | 2019 | 31 | |
| 3 | 2018 | 31 | |
| 4 | 2013 | 24 | |
| 5 | 2023 | 21 | |
| 6 | 2019 | 16 | |
| 7 | 2019 | 15 | |
| 8 | 2017 | 10 | |
| 9 | 2014 | 10 | |
| 10 | 2020 | 5 | |
| 11 | 2014 | 4 | |
| 12 | 2015 | 4 | |
| 13 | 2014 | 3 | |
| 14 | 2023 | 1 | |
| 15 | 2013 | 1 | |
| 16 | 2025 | 0 |
About Abel Chandra
Abel Chandra is a scholar working on Molecular Biology, Computer Networks and Communications, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Surgery, having authored 16 papers that have together received 272 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (8 papers), RNA and protein synthesis mechanisms (4 papers), Genomics and Phylogenetic Studies (4 papers), IoT-based Smart Home Systems (3 papers), Protein Structure and Dynamics (3 papers), IoT and Edge/Fog Computing (3 papers), Energy Efficient Wireless Sensor Networks (1 paper) and Internet of Things and Social Network Interactions (1 paper). The work is most often cited by research in Molecular Biology (184 citations), Computational Theory and Mathematics (34 citations), Clinical Biochemistry (12 citations), Microbiology (10 citations) and Health Informatics (2 citations). Abel Chandra has collaborated with scholars based in Fiji, Japan and United States. Frequent co-authors include Regina Grätz, Tommy Löfstedt, Abdollah Dehzangi, Alok Sharma, Tatsuhiko Tsunoda, Seong Ro Lee, Daichi Shigemizu, Sang Hyeok Park, Anjeela D. Jokhan and Shoba Ranganathan. Their work appears in journals such as Scientific Reports, BMC Genomics, BMC Bioinformatics, eLife and Genes.
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.