Yuri Nikolsky
- Molecular Biology top 5%
- Computational Theory and Mathematics top 0.5%
- Oncology top 5%
- Cancer Research top 5%
- Genetics top 10%
- Co-authors
- Tatiana NikolskayaAndrej BugrimSean EkinsEugene KirillovDouglas K. BishopDavid LydallTed WeinertMarina Bessarabova
- Topics
- Computational Drug Discovery Methods (20 papers)Bioinformatics and Genomic Networks (19 papers)Gene expression and cancer classification (11 papers)
- Partner nations
- United StatesRussiaSwitzerland
In The Last Decade
Yuri Nikolsky
55 papers receiving 3.6k citations
Peers
Comparison fields: 5 of 158
- Molecular Biology 2.3k
- Computational Theory and Mathematics 633
- Oncology 622
- Cancer Research 595
- Genetics 331
Countries citing papers authored by Yuri Nikolsky
This map shows the geographic impact of Yuri Nikolsky'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 Yuri Nikolsky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuri Nikolsky more than expected).
Fields of papers citing papers by Yuri Nikolsky
This network shows the impact of papers produced by Yuri Nikolsky. 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 Yuri Nikolsky. The network helps show where Yuri Nikolsky may publish in the future.
Co-authorship network of co-authors of Yuri Nikolsky
This figure shows the co-authorship network connecting the top 25 collaborators of Yuri Nikolsky. A scholar is included among the top collaborators of Yuri Nikolsky 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 Yuri Nikolsky. Yuri Nikolsky is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 96 | |
| 2 | 19 | |
| 3 | 93 | |
| 4 | 72 | |
| 5 | 55 | |
| 6 | 8 | |
| 7 | 18 | |
| 8 | 6 | |
| 9 | 80 | |
| 10 | 155 | |
| 11 | 3 | |
| 12 | 63 | |
| 13 | 8 | |
| 14 | 30 | |
| 15 | 69 | |
| 16 | 71 | |
| 17 | 381 | |
| 18 | Increased dietary cholesterol-induced atherosclerosis is associated with liver inflammation: Identification of novel regulatory pathways and transcriptional regulators involved in switch from metabolic adaptation to inflammatory state. | 1 |
| 19 | 38 | |
| 20 | 282 |
About Yuri Nikolsky
Yuri Nikolsky is a scholar working on Computational Theory and Mathematics, Molecular Biology and Pharmacology, having authored 55 papers that have together received 3.6k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (20 papers), Bioinformatics and Genomic Networks (19 papers) and Gene expression and cancer classification (11 papers). The work is most often cited by research in Computational Theory and Mathematics (633 citations), Cancer Research (595 citations) and Molecular Biology (2.3k citations). Yuri Nikolsky has collaborated with scholars based in United States, Russia and Switzerland. Frequent co-authors include Tatiana Nikolskaya, Andrej Bugrim, Sean Ekins, Eugene Kirillov, Douglas K. Bishop, David Lydall, Ted Weinert, Marina Bessarabova, Kornélia Polyák and Eugene A. Rakhmatulin. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences 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.