Anchala Kumari
- Molecular Biology
- Infectious Diseases
- Computational Theory and Mathematics top 5%
- Physiology
- Organic Chemistry
- Co-authors
- Abhinav GroverAditi SinghPallavi SomvanshiSonam GroverSukriti GoyalSalma JamalBharati PandeyNeeraj Kumar
- Topics
- Computational Drug Discovery Methods (9 papers)Alzheimer's disease research and treatments (8 papers)Protein Structure and Dynamics (5 papers)
- Partner nations
- IndiaRussiaDemocratic Republic of the Congo
In The Last Decade
Anchala Kumari
29 papers receiving 436 citations
Peers
Comparison fields: 5 of 90
- Molecular Biology 227
- Infectious Diseases 97
- Computational Theory and Mathematics 94
- Physiology 80
- Organic Chemistry 45
Countries citing papers authored by Anchala Kumari
This map shows the geographic impact of Anchala Kumari'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 Anchala Kumari with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anchala Kumari more than expected).
Fields of papers citing papers by Anchala Kumari
This network shows the impact of papers produced by Anchala Kumari. 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 Anchala Kumari. The network helps show where Anchala Kumari may publish in the future.
Co-authorship network of co-authors of Anchala Kumari
This figure shows the co-authorship network connecting the top 25 collaborators of Anchala Kumari. A scholar is included among the top collaborators of Anchala Kumari 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 Anchala Kumari. Anchala Kumari is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 24 | |
| 5 | 13 | |
| 6 | 7 | |
| 7 | 61 | |
| 8 | 5 | |
| 9 | 27 | |
| 10 | 4 | |
| 11 | 7 | |
| 12 | 32 | |
| 13 | 24 | |
| 14 | A mathematical model for multi product-multi supplier-multi period inventory lot size problem (MMMILP) with supplier selection in supply chain system | 0 |
| 15 | 14 | |
| 16 | 4 | |
| 17 | 19 | |
| 18 | 29 | |
| 19 | 18 | |
| 20 | 3 |
About Anchala Kumari
Anchala Kumari is a scholar working on Computational Theory and Mathematics, Infectious Diseases and Discrete Mathematics and Combinatorics, having authored 31 papers that have together received 441 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (9 papers), Alzheimer's disease research and treatments (8 papers) and Protein Structure and Dynamics (5 papers). The work is most often cited by research in Biological Psychiatry (17 citations), Computational Theory and Mathematics (94 citations) and Infectious Diseases (97 citations). Anchala Kumari has collaborated with scholars based in India, Russia and Democratic Republic of the Congo. Frequent co-authors include Abhinav Grover, Aditi Singh, Pallavi Somvanshi, Sonam Grover, Sukriti Goyal, Salma Jamal, Bharati Pandey, Neeraj Kumar, Damini Sood and Ritika Sharma. Their work appears in journals such as PLoS ONE, Scientific Reports and International Journal of Pharmaceutics.
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.