Divya Singhal
Impact in
- Bioengineering top 5%
- Analytical Chemistry and Sensors
- Spectroscopy top 5%
- Molecular Sensors and Ion Detection
Papers in
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- Advanced biosensing and bioanalysis techniques 3
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- Molecular Sensors and Ion Detection 6
- Co-authors
- Neha Gupta (3 shared papers)Ashok Kumar Singh (3 shared papers)John D. England (1 shared paper)Rima El‐Abassi (1 shared paper)Vijay Kumar (2 shared papers)Pramod Kumar (1 shared paper)Sushil Kumar (1 shared paper)Rajeev Gupta (1 shared paper)
- Journals
- New Journal of Chemistry (3 papers)Indian Journal of Pharmaceutical Sciences (2 papers)Journal of the Neurological Sciences (1 paper)Neurology (1 paper)RSC Advances (1 paper)
- Partner nations
- IndiaUnited StatesSaudi Arabia
In The Last Decade
Divya Singhal
23 papers receiving 494 citations
Peers
Comparison fields: 5 of 85
- Bioengineering 84
- Spectroscopy 246
- Electrochemistry 80
- Physiology 87
- Materials Chemistry 127
Countries citing papers authored by Divya Singhal
This map shows the geographic impact of Divya Singhal'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 Divya Singhal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Divya Singhal more than expected).
Fields of papers citing papers by Divya Singhal
This network shows the impact of papers produced by Divya Singhal. 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 Divya Singhal. The network helps show where Divya Singhal may publish in the future.
Co-authors
The 25 scholars most cited alongside Divya Singhal, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 107 | |
| 2 | 2014 | 103 | |
| 3 | 2015 | 71 | |
| 4 | 2017 | 39 | |
| 5 | 2016 | 37 | |
| 6 | 2020 | 31 | |
| 7 | 2022 | 30 | |
| 8 | 2013 | 15 | |
| 9 | 2017 | 15 | |
| 10 | In-silico single nucleotide polymorphisms (SNP) mining of Sorghum bicolor genome | 2011 | 12 |
| 11 | 2020 | 10 | |
| 12 | 2019 | 8 | |
| 13 | 2019 | 6 | |
| 14 | 2015 | 6 | |
| 15 | 2023 | 4 | |
| 16 | 2023 | 3 | |
| 17 | 2012 | 2 | |
| 18 | 2023 | 2 | |
| 19 | 2017 | 2 | |
| 20 | 2020 | 1 |
About Divya Singhal
Divya Singhal is a scholar working on Molecular Biology, Spectroscopy, Rheumatology, Biotechnology and Materials Chemistry, having authored 25 papers that have together received 507 indexed citations. Recurring topics across this work include Molecular Sensors and Ion Detection (6 papers), Luminescence and Fluorescent Materials (3 papers), Advanced biosensing and bioanalysis techniques (3 papers), Pharmacological Effects and Toxicity Studies (2 papers), Electrochemical Analysis and Applications (2 papers), Microbial Metabolism and Applications (2 papers), Analytical Chemistry and Sensors (2 papers) and Adolescent and Pediatric Healthcare (1 paper). The work is most often cited by research in Bioengineering (84 citations), Spectroscopy (246 citations), Electrochemistry (80 citations), Physiology (87 citations) and Materials Chemistry (127 citations). Divya Singhal has collaborated with scholars based in India, United States and Saudi Arabia. Frequent co-authors include Neha Gupta, Ashok Kumar Singh, John D. England, Rima El‐Abassi, Vijay Kumar, Pramod Kumar, Sushil Kumar, Rajeev Gupta, Sanjai Saxena and Joseph R. Berger. Their work appears in journals such as New Journal of Chemistry, Indian Journal of Pharmaceutical Sciences, Journal of the Neurological Sciences, Neurology and RSC Advances.
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.