Allam Appa Rao
- Molecular Biology
- Pharmacology top 10%
- Physiology
- Computational Theory and Mathematics top 5%
- Endocrinology, Diabetes and Metabolism
- Co-authors
- Undurti N. DasGR SridharSrinubabu GedelaP. Venkateswara RaoAmit KumarVinit Kumar GunjanK. SrinivasPooja Pooja
- Topics
- Computational Drug Discovery Methods (13 papers)Cholinesterase and Neurodegenerative Diseases (10 papers)Bioinformatics and Genomic Networks (8 papers)
- Journals
- Current Pharmaceutical DesignAdvances in experimental medicine and biologyJournal of Chromatography B
- Partner nations
- IndiaUnited StatesAustralia
In The Last Decade
Allam Appa Rao
59 papers receiving 594 citations
Peers
Comparison fields: 5 of 125
- Molecular Biology 212
- Pharmacology 166
- Physiology 102
- Computational Theory and Mathematics 92
- Endocrinology, Diabetes and Metabolism 89
Countries citing papers authored by Allam Appa Rao
This map shows the geographic impact of Allam Appa Rao'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 Allam Appa Rao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Allam Appa Rao more than expected).
Fields of papers citing papers by Allam Appa Rao
This network shows the impact of papers produced by Allam Appa Rao. 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 Allam Appa Rao. The network helps show where Allam Appa Rao may publish in the future.
Co-authorship network of co-authors of Allam Appa Rao
This figure shows the co-authorship network connecting the top 25 collaborators of Allam Appa Rao. A scholar is included among the top collaborators of Allam Appa Rao 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 Allam Appa Rao. Allam Appa Rao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 4 | |
| 3 | 2 | |
| 4 | 21 | |
| 5 | 26 | |
| 6 | 3 | |
| 7 | 20 | |
| 8 | 1 | |
| 9 | 10 | |
| 10 | 27 | |
| 11 | 5 | |
| 12 | Biological Early Brain Cancer Detection Using Artificial Neural Network. | 11 |
| 13 | 16 | |
| 14 | 8 | |
| 15 | 6 | |
| 16 | 152 | |
| 17 | 12 | |
| 18 | 11 | |
| 19 | 18 | |
| 20 | 6 |
About Allam Appa Rao
Allam Appa Rao is a scholar working on Computational Theory and Mathematics, Pharmacology and Health Information Management, having authored 65 papers that have together received 658 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (13 papers), Cholinesterase and Neurodegenerative Diseases (10 papers) and Bioinformatics and Genomic Networks (8 papers). The work is most often cited by research in Health Information Management (52 citations), Pharmacology (166 citations) and Drug Discovery (1 citation). Allam Appa Rao has collaborated with scholars based in India, United States and Australia. Frequent co-authors include Undurti N. Das, GR Sridhar, Srinubabu Gedela, P. Venkateswara Rao, Amit Kumar, Vinit Kumar Gunjan, K. Srinivas, Pooja Pooja, Monika Kumari and R.S. Rathore. Their work appears in journals such as Current Pharmaceutical Design, Advances in experimental medicine and biology and Journal of Chromatography B.
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.