Ivan Anishchenko
- Molecular Biology top 5%
- Protein Structure and Dynamics 25
- Machine Learning in Bioinformatics 6
- Bioinformatics and Genomic Networks 6
- Genomics and Phylogenetic Studies 6
- Microbial Metabolic Engineering and Bioproduction 6
- RNA and protein synthesis mechanisms 5
- Structural Biology top 5%
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- Computational Drug Discovery Methods 5
- Biotechnology top 5%
- Materials Chemistry top 10%
- Enzyme Structure and Function 13
- Co-authors
- David BakerSergey OvchinnikovZhenling PengJianyi YangHahnbeom ParkMinkyung BaekFrank DiMaioQian Cong
- Journals
- Proteins Structure Function and Bioinformatics (11 papers)Proceedings of the National Academy of Sciences (4 papers)Nature Methods (2 papers)
- Partner nations
- United StatesBelarusChina
In The Last Decade
Ivan Anishchenko
35 papers receiving 3.0k citations
Hit Papers
Peers
Comparison fields: 5 of 146
- Molecular Biology 2.5k
- Structural Biology 34
- Computational Theory and Mathematics 372
- Biotechnology 118
- Materials Chemistry 598
Countries citing papers authored by Ivan Anishchenko
This map shows the geographic impact of Ivan Anishchenko'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 Ivan Anishchenko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ivan Anishchenko more than expected).
Fields of papers citing papers by Ivan Anishchenko
This network shows the impact of papers produced by Ivan Anishchenko. 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 Ivan Anishchenko. The network helps show where Ivan Anishchenko may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ivan Anishchenko, 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 | 2025 | 3 | |
| 2 | Atomic context-conditioned protein sequence design using LigandMPNNbreakdown → | 2025 | 39 |
| 3 | 2024 | 14 | |
| 4 | Accurate prediction of protein–nucleic acid complexes using RoseTTAFoldNAbreakdown → | 2023 | 176 |
| 5 | De novo design of luciferases using deep learningbreakdown → | 2023 | 241 |
| 6 | 2022 | 17 | |
| 7 | De novo protein design by deep network hallucinationbreakdown → | 2021 | 334 |
| 8 | Improved protein structure refinement guided by deep learning based accuracy estimationbreakdown → | 2021 | 157 |
| 9 | The trRosetta server for fast and accurate protein structure predictionbreakdown → | 2021 | 434 |
| 10 | 2021 | 2 | |
| 11 | 2021 | 17 | |
| 12 | 2020 | 23 | |
| 13 | Improved protein structure prediction using predicted interresidue orientationsbreakdown → | 2020 | 925 |
| 14 | 2020 | 11 | |
| 15 | Protein interaction networks revealed by proteome coevolutionbreakdown → | 2019 | 150 |
| 16 | 2019 | 25 | |
| 17 | 2018 | 17 | |
| 18 | 2017 | 132 | |
| 19 | 2011 | 1 | |
| 20 | 2010 | 2 |
About Ivan Anishchenko
Ivan Anishchenko is a scholar working on Virology, Structural Biology and Molecular Biology, having authored 37 papers that have together received 3.1k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (25 papers), Enzyme Structure and Function (13 papers), Machine Learning in Bioinformatics (6 papers), Bioinformatics and Genomic Networks (6 papers), Genomics and Phylogenetic Studies (6 papers), Microbial Metabolic Engineering and Bioproduction (6 papers), Computational Drug Discovery Methods (5 papers) and RNA and protein synthesis mechanisms (5 papers). The work is most often cited by research in Molecular Biology (2.5k citations), Structural Biology (34 citations) and Computational Theory and Mathematics (372 citations). Ivan Anishchenko has collaborated with scholars based in United States, Belarus and China. Frequent co-authors include David Baker, Sergey Ovchinnikov, Zhenling Peng, Jianyi Yang, Hahnbeom Park, Minkyung Baek, Frank DiMaio, Qian Cong, Justas Dauparas and Hong Su. Their work appears in journals such as Proteins Structure Function and Bioinformatics, Proceedings of the National Academy of Sciences, Nature Methods, Journal of Biomolecular Structure and Dynamics and Nature.
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.