Siddharth Sinha
Impact in
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- Liver physiology and pathology
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- Computational Drug Discovery Methods
Papers in
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- CRISPR and Genetic Engineering 4
- Genomics and Phylogenetic Studies 3
- RNA and protein synthesis mechanisms 2
- Oncology 5
- Cancer-related Molecular Pathways 2
- Co-authors
- San Ming Wang (15 shared papers)Benjamin Tam (8 shared papers)Abhinav Grover (6 shared papers)Pallavi Somvanshi (4 shared papers)Arpit Tandon (1 shared paper)Anil Dhawan (2 shared papers)Emer Fitzpatrick (2 shared papers)Aditi Singh (4 shared papers)
- Journals
- Journal of Cellular Biochemistry (2 papers)BMC Genomics (2 papers)Journal of Molecular Medicine (2 papers)International Journal of Molecular Sciences (2 papers)International Journal of Cancer (2 papers)
- Partner nations
- MacaoIndiaUnited States
In The Last Decade
Siddharth Sinha
29 papers receiving 530 citations
Peers
Comparison fields: 5 of 89
- Hepatology 40
- Computational Theory and Mathematics 69
- Molecular Biology 264
- Molecular Medicine 19
- Genetics 87
Countries citing papers authored by Siddharth Sinha
This map shows the geographic impact of Siddharth Sinha'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 Siddharth Sinha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Siddharth Sinha more than expected).
Fields of papers citing papers by Siddharth Sinha
This network shows the impact of papers produced by Siddharth Sinha. 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 Siddharth Sinha. The network helps show where Siddharth Sinha may publish in the future.
Co-authors
The 25 scholars most cited alongside Siddharth Sinha, 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 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 66 | |
| 2 | 2020 | 65 | |
| 3 | 2019 | 59 | |
| 4 | 2018 | 53 | |
| 5 | 2020 | 38 | |
| 6 | 2017 | 37 | |
| 7 | 2011 | 32 | |
| 8 | 2015 | 28 | |
| 9 | 2017 | 19 | |
| 10 | 2021 | 17 | |
| 11 | 2015 | 16 | |
| 12 | 2017 | 15 | |
| 13 | 2021 | 9 | |
| 14 | 2019 | 9 | |
| 15 | 2019 | 8 | |
| 16 | 2021 | 8 | |
| 17 | 2021 | 7 | |
| 18 | 2022 | 7 | |
| 19 | 2018 | 6 | |
| 20 | 2024 | 6 |
About Siddharth Sinha
Siddharth Sinha is a scholar working on Molecular Biology, Oncology, Genetics, Infectious Diseases and Surgery, having authored 30 papers that have together received 531 indexed citations. Recurring topics across this work include BRCA gene mutations in cancer (5 papers), CRISPR and Genetic Engineering (4 papers), Genomics and Phylogenetic Studies (3 papers), Liver physiology and pathology (2 papers), Cancer-related Molecular Pathways (2 papers), RNA and protein synthesis mechanisms (2 papers), Tuberculosis Research and Epidemiology (2 papers) and Genomics and Rare Diseases (2 papers). The work is most often cited by research in Hepatology (40 citations), Computational Theory and Mathematics (69 citations), Molecular Biology (264 citations), Molecular Medicine (19 citations) and Genetics (87 citations). Siddharth Sinha has collaborated with scholars based in Macao, India and United States. Frequent co-authors include San Ming Wang, Benjamin Tam, Abhinav Grover, Pallavi Somvanshi, Arpit Tandon, Anil Dhawan, Emer Fitzpatrick, Aditi Singh, Sukriti Goyal and Salma Jamal. Their work appears in journals such as Journal of Cellular Biochemistry, BMC Genomics, Journal of Molecular Medicine, International Journal of Molecular Sciences and International Journal of Cancer.
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.