Amit Aggarwal
- Co-authors
- Neeru JindalPatrick TanNidhi SinglaWilbur B. BowneKent‐Man ChuDavid D.L. BowtellJesús EsquivelYujin Hoshida
- Topics
- Gene expression and cancer classification (4 papers)Cytomegalovirus and herpesvirus research (3 papers)Liver Disease Diagnosis and Treatment (2 papers)
- Journals
- SHILAP Revista de lepidopterologíaCancer ResearchHuman Molecular Genetics
- Partner nations
- IndiaSingaporeUnited States
In The Last Decade
Amit Aggarwal
23 papers receiving 367 citations
Peers
Comparison fields: 5 of 89
- Molecular Biology 118
- Epidemiology 108
- Infectious Diseases 81
- Oncology 64
- Cancer Research 64
Countries citing papers authored by Amit Aggarwal
This map shows the geographic impact of Amit Aggarwal'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 Amit Aggarwal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amit Aggarwal more than expected).
Fields of papers citing papers by Amit Aggarwal
This network shows the impact of papers produced by Amit Aggarwal. 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 Amit Aggarwal. The network helps show where Amit Aggarwal may publish in the future.
Co-authorship network of co-authors of Amit Aggarwal
This figure shows the co-authorship network connecting the top 25 collaborators of Amit Aggarwal. A scholar is included among the top collaborators of Amit Aggarwal 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 Amit Aggarwal. Amit Aggarwal 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 | 4 | |
| 3 | 5 | |
| 4 | 33 | |
| 5 | COMPARATIVE ANALYSIS OF ANTI-INFLAMMATORY ACTIVITY OF AQUEOUS AND METHANOLIC EXTRACTS OF C. CASSIA AND C. ZEYLANICUM IN RAW264.7, SW1353 AND PRIMARY CHONDROCYTES | 4 |
| 6 | 30 | |
| 7 | 13 | |
| 8 | 2 | |
| 9 | 10 | |
| 10 | 1 | |
| 11 | 69 | |
| 12 | 1 | |
| 13 | 20 | |
| 14 | 38 | |
| 15 | 8 | |
| 16 | 32 | |
| 17 | 5 | |
| 18 | 42 | |
| 19 | Feasibility of using low-volume tissue samples for gene expression profiling of advanced non-small cell lung cancers. | 27 |
| 20 | Type B lactic acidosis in an AIDS patient treated with zidovudine. | 18 |
About Amit Aggarwal
Amit Aggarwal is a scholar working on Infectious Diseases, Hepatology and Epidemiology, having authored 23 papers that have together received 391 indexed citations. Recurring topics across this work include Gene expression and cancer classification (4 papers), Cytomegalovirus and herpesvirus research (3 papers) and Liver Disease Diagnosis and Treatment (2 papers). The work is most often cited by research in Infectious Diseases (81 citations), Cancer Research (64 citations) and Epidemiology (108 citations). Amit Aggarwal has collaborated with scholars based in India, Singapore and United States. Frequent co-authors include Neeru Jindal, Patrick Tan, Nidhi Singla, Wilbur B. Bowne, Kent‐Man Chu, David D.L. Bowtell, Jesús Esquivel, Yujin Hoshida, Xin Chen and Scott D. Richard. Their work appears in journals such as SHILAP Revista de lepidopterología, Cancer Research and Human Molecular Genetics.
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.