Sergey Nikolenko
- Molecular Biology top 0.2%
- Ecology top 0.1%
- Plant Science top 0.5%
- Molecular Medicine top 0.05%
- Endocrinology top 0.05%
- Co-authors
- Max A. AlekseyevAlexander SirotkinPavel A. PevznerAlexey GurevichAlexander S. KulikovDmitry AntipovSergey NurkGlenn Tesler
- Topics
- Topic Modeling (24 papers)Software-Defined Networks and 5G (15 papers)Natural Language Processing Techniques (15 papers)
- Partner nations
- RussiaSpainUnited States
In The Last Decade
Sergey Nikolenko
105 papers receiving 20.9k citations
Hit Papers
Peers
Comparison fields: 5 of 213
- Molecular Biology 10.3k
- Ecology 5.4k
- Plant Science 3.7k
- Molecular Medicine 2.4k
- Endocrinology 2.4k
Countries citing papers authored by Sergey Nikolenko
This map shows the geographic impact of Sergey Nikolenko'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 Sergey Nikolenko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sergey Nikolenko more than expected).
Fields of papers citing papers by Sergey Nikolenko
This network shows the impact of papers produced by Sergey Nikolenko. 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 Sergey Nikolenko. The network helps show where Sergey Nikolenko may publish in the future.
Co-authorship network of co-authors of Sergey Nikolenko
This figure shows the co-authorship network connecting the top 25 collaborators of Sergey Nikolenko. A scholar is included among the top collaborators of Sergey Nikolenko 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 Sergey Nikolenko. Sergey Nikolenko is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 1 | |
| 8 | 14 | |
| 9 | AspeRa: Aspect-Based Rating Prediction Based on User Reviews | 1 |
| 10 | 48 | |
| 11 | Concorde: Morphological Agreement in Conversational Models | 0 |
| 12 | Measuring Prejudice and Ethnic Tensions in User-Generated Content | 4 |
| 13 | Who’s Bad? Attitudes Toward Resettlers From the Post-Soviet South Versus Other Nations in the Russian Blogosphere | 8 |
| 14 | Improving neural network models for natural language processing in russian with synonyms | 7 |
| 15 | FDR-controlled metabolite annotation for high-resolution imaging mass spectrometrybreakdown → | 334 |
| 16 | ARTM vs. LDA: an SVD Extension Case Study | 1 |
| 17 | Predicting the age of social network users from user-generated texts with word embeddings | 3 |
| 18 | 1 | |
| 19 | SPAdes: A New Genome Assembly Algorithm and Its Applications to Single-Cell Sequencingbreakdown → | 17957 |
| 20 | A New Bayesian Rating System for Team Competitions | 6 |
About Sergey Nikolenko
Sergey Nikolenko is a scholar working on Hardware and Architecture, Computer Networks and Communications and Artificial Intelligence, having authored 123 papers that have together received 21.2k indexed citations. Recurring topics across this work include Topic Modeling (24 papers), Software-Defined Networks and 5G (15 papers) and Natural Language Processing Techniques (15 papers). The work is most often cited by research in Molecular Medicine (2.4k citations), Endocrinology (2.4k citations) and Ecology (5.4k citations). Sergey Nikolenko has collaborated with scholars based in Russia, Spain and United States. Frequent co-authors include Max A. Alekseyev, Alexander Sirotkin, Pavel A. Pevzner, Alexey Gurevich, Alexander S. Kulikov, Dmitry Antipov, Sergey Nurk, Glenn Tesler, Son Pham and Andrey D. Prjibelski. Their work appears in journals such as Bioinformatics, Analytical Chemistry and Applied and Environmental Microbiology.
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.