Ravina Khandelwal
- Molecular Biology
- Computational Theory and Mathematics top 5%
- Organic Chemistry
- Pathology and Forensic Medicine
- Oncology
- Co-authors
- Sanjeev Kumar SinghAnuraj NayarisseriDiksha SharmaTajamul HussainPoonam TanwarAlejandro Speck‐PlancheKhushboo SharmaSugunakar Vuree
- Topics
- Computational Drug Discovery Methods (6 papers)Synthesis and biological activity (3 papers)Lung Cancer Treatments and Mutations (3 papers)
- Partner nations
- IndiaSaudi ArabiaChile
In The Last Decade
Ravina Khandelwal
14 papers receiving 251 citations
Peers
Comparison fields: 5 of 67
- Molecular Biology 135
- Computational Theory and Mathematics 121
- Organic Chemistry 44
- Pathology and Forensic Medicine 34
- Oncology 31
Countries citing papers authored by Ravina Khandelwal
This map shows the geographic impact of Ravina Khandelwal'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 Ravina Khandelwal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ravina Khandelwal more than expected).
Fields of papers citing papers by Ravina Khandelwal
This network shows the impact of papers produced by Ravina Khandelwal. 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 Ravina Khandelwal. The network helps show where Ravina Khandelwal may publish in the future.
Co-authorship network of co-authors of Ravina Khandelwal
This figure shows the co-authorship network connecting the top 25 collaborators of Ravina Khandelwal. A scholar is included among the top collaborators of Ravina Khandelwal based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ravina Khandelwal. Ravina Khandelwal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 16 | |
| 2 | 63 | |
| 3 | 6 | |
| 4 | 27 | |
| 5 | 7 | |
| 6 | 11 | |
| 7 | 10 | |
| 8 | 22 | |
| 9 | 14 | |
| 10 | 23 | |
| 11 | 0 | |
| 12 | 15 | |
| 13 | 12 | |
| 14 | 22 | |
| 15 | A Computer - Aided Drug Designing for Pharmacological inhibition of ALK inhibitors induces apoptosis and differentiation in Non-small cell lung cancer | 5 |
About Ravina Khandelwal
Ravina Khandelwal is a scholar working on Computational Theory and Mathematics, Pathology and Forensic Medicine and Hematology, having authored 15 papers that have together received 253 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (6 papers), Synthesis and biological activity (3 papers) and Lung Cancer Treatments and Mutations (3 papers). The work is most often cited by research in Computational Theory and Mathematics (121 citations), Health Informatics (4 citations) and Molecular Biology (135 citations). Ravina Khandelwal has collaborated with scholars based in India, Saudi Arabia and Chile. Frequent co-authors include Sanjeev Kumar Singh, Anuraj Nayarisseri, Diksha Sharma, Tajamul Hussain, Poonam Tanwar, Alejandro Speck‐Planche, Khushboo Sharma, Sugunakar Vuree, Umesh Panwar and Chandrabose Selvaraj. Their work appears in journals such as Current Topics in Medicinal Chemistry, Current Drug Targets and Journal of Molecular Modeling.
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.