Avinash Sahu
Impact in
- Cancer Research top 1%
- Cancer-related molecular mechanisms research
- Oncology top 2%
- Cancer Immunotherapy and Biomarkers
Papers in
-
- Bioinformatics and Genomic Networks 3
- Gene expression and cancer classification 3
- Oncology 9
- CAR-T cell therapy research 4
- Cancer Immunotherapy and Biomarkers 3
- Cytokine Signaling Pathways and Interactions 2
- Co-authors
- Jingxin Fu (4 shared papers)X. Shirley Liu (4 shared papers)Shengqing Gu (4 shared papers)Bo Li (3 shared papers)Xihao Hu (3 shared papers)Jun Liu (2 shared papers)Deng Pan (2 shared papers)Gordon J. Freeman (2 shared papers)
- Journals
- PLoS ONE (2 papers)Genomics Proteomics & Bioinformatics (1 paper)Nature Medicine (1 paper)Cancer Immunology Research (1 paper)Nature Communications (1 paper)
- Partner nations
- United StatesChinaIsrael
In The Last Decade
Avinash Sahu
19 papers receiving 3.6k citations
Hit Papers
Peers
Comparison fields: 5 of 83
- Cancer Research 1.3k
- Oncology 1.6k
- Pulmonary and Respiratory Medicine 1.9k
- Immunology 987
- Molecular Biology 1.8k
Countries citing papers authored by Avinash Sahu
This map shows the geographic impact of Avinash Sahu'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 Avinash Sahu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Avinash Sahu more than expected).
Fields of papers citing papers by Avinash Sahu
This network shows the impact of papers produced by Avinash Sahu. 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 Avinash Sahu. The network helps show where Avinash Sahu may publish in the future.
Co-authors
The 25 scholars most cited alongside Avinash Sahu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response Hit paper breakdown → | 2018 | 3242 |
| 2 | 2018 | 115 | |
| 3 | 2019 | 68 | |
| 4 | 2023 | 49 | |
| 5 | 2017 | 30 | |
| 6 | 2019 | 28 | |
| 7 | 2019 | 25 | |
| 8 | 2012 | 24 | |
| 9 | 2020 | 15 | |
| 10 | 2023 | 12 | |
| 11 | 2014 | 9 | |
| 12 | 2024 | 8 | |
| 13 | 2024 | 7 | |
| 14 | 2019 | 7 | |
| 15 | 2019 | 3 | |
| 16 | 2012 | 3 | |
| 17 | 2021 | 2 | |
| 18 | 2023 | 2 | |
| 19 | 2023 | 2 | |
| 20 | 2018 | 0 |
About Avinash Sahu
Avinash Sahu is a scholar working on Molecular Biology, Oncology, Immunology, Genetics and Cancer Research, having authored 20 papers that have together received 3.7k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (5 papers), CAR-T cell therapy research (4 papers), Ferroptosis and cancer prognosis (3 papers), Cancer Immunotherapy and Biomarkers (3 papers), Cancer Genomics and Diagnostics (3 papers), Bioinformatics and Genomic Networks (3 papers), Gene expression and cancer classification (3 papers) and Cytokine Signaling Pathways and Interactions (2 papers). The work is most often cited by research in Cancer Research (1.3k citations), Oncology (1.6k citations), Pulmonary and Respiratory Medicine (1.9k citations), Immunology (987 citations) and Molecular Biology (1.8k citations). Avinash Sahu has collaborated with scholars based in United States, China and Israel. Frequent co-authors include Jingxin Fu, X. Shirley Liu, Shengqing Gu, Bo Li, Xihao Hu, Jun Liu, Deng Pan, Gordon J. Freeman, Kai W. Wucherpfennig and Nicole Traugh. Their work appears in journals such as PLoS ONE, Genomics Proteomics & Bioinformatics, Nature Medicine, Cancer Immunology Research and Nature Communications.
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.