Ashwin Unnikrishnan
Impact in
- Aging top 5%
- Genetics, Aging, and Longevity in Model Organisms
- Hematology top 5%
- Acute Myeloid Leukemia Research
Papers in
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- DNA Repair Mechanisms 4
- RNA Research and Splicing 4
- Genomics and Chromatin Dynamics 4
-
- Acute Myeloid Leukemia Research 7
- Chronic Myeloid Leukemia Treatments 3
- Co-authors
- Toshio Tsukiyama (2 shared papers)Philip R. Gafken (1 shared paper)John E. Pimanda (11 shared papers)A. R. Heydari (1 shared paper)Arlan Richardson (1 shared paper)Julie A.I. Thoms (6 shared papers)Jason W.H. Wong (5 shared papers)Pramod Koshy (3 shared papers)
- Journals
- Leukemia (4 papers)Blood (3 papers)Nucleic Acids Research (2 papers)Bioinformatics (1 paper)Methods (1 paper)
- Partner nations
- AustraliaUnited StatesSweden
In The Last Decade
Ashwin Unnikrishnan
19 papers receiving 700 citations
Peers
Comparison fields: 5 of 86
- Aging 42
- Hematology 150
- Molecular Biology 475
- Cancer Research 71
- Geriatrics and Gerontology 10
Countries citing papers authored by Ashwin Unnikrishnan
This map shows the geographic impact of Ashwin Unnikrishnan'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 Ashwin Unnikrishnan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ashwin Unnikrishnan more than expected).
Fields of papers citing papers by Ashwin Unnikrishnan
This network shows the impact of papers produced by Ashwin Unnikrishnan. 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 Ashwin Unnikrishnan. The network helps show where Ashwin Unnikrishnan may publish in the future.
Co-authors
The 25 scholars most cited alongside Ashwin Unnikrishnan, 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 | 2010 | 155 | |
| 2 | 2013 | 107 | |
| 3 | 2007 | 98 | |
| 4 | 2016 | 58 | |
| 5 | 2022 | 49 | |
| 6 | 2018 | 42 | |
| 7 | 2022 | 40 | |
| 8 | 2019 | 23 | |
| 9 | 2017 | 22 | |
| 10 | 2011 | 18 | |
| 11 | 2022 | 18 | |
| 12 | 2014 | 18 | |
| 13 | 2016 | 16 | |
| 14 | 2020 | 15 | |
| 15 | 2022 | 10 | |
| 16 | 2012 | 9 | |
| 17 | 2018 | 6 | |
| 18 | 2022 | 4 | |
| 19 | 2018 | 2 |
About Ashwin Unnikrishnan
Ashwin Unnikrishnan is a scholar working on Molecular Biology, Hematology, Genetics, Cancer Research and Public Health, Environmental and Occupational Health, having authored 19 papers that have together received 710 indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (7 papers), DNA Repair Mechanisms (4 papers), RNA Research and Splicing (4 papers), Genomics and Chromatin Dynamics (4 papers), Chronic Myeloid Leukemia Treatments (3 papers), Cancer Genomics and Diagnostics (2 papers), Acute Lymphoblastic Leukemia research (2 papers) and Advanced Nanomaterials in Catalysis (2 papers). The work is most often cited by research in Aging (42 citations), Hematology (150 citations), Molecular Biology (475 citations), Cancer Research (71 citations) and Geriatrics and Gerontology (10 citations). Ashwin Unnikrishnan has collaborated with scholars based in Australia, United States and Sweden. Frequent co-authors include Toshio Tsukiyama, Philip R. Gafken, John E. Pimanda, A. R. Heydari, Arlan Richardson, Julie A.I. Thoms, Jason W.H. Wong, Pramod Koshy, Jia‐Lin Yang and Dominik Beck. Their work appears in journals such as Leukemia, Blood, Nucleic Acids Research, Bioinformatics and Methods.
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.