| Assessment of k-mer spectrum applicability for metagenomic dissimilarity analysis VB Dubinkina, DS Ischenko, VI Ulyantsev, AV Tyakht, DG Alexeev BMC bioinformatics 17, 1-11, 2016 | 94 | 2016 |
| MoG-VQE: Multiobjective genetic variational quantum eigensolver D Chivilikhin, A Samarin, V Ulyantsev, I Iorsh, AR Oganov, O Kyriienko arXiv preprint arXiv:2007.04424, 2020 | 83 | 2020 |
| GADMA: Genetic algorithm for inferring demographic history of multiple populations from allele frequency spectrum data E Noskova, V Ulyantsev, KP Koepfli, SJ O'brien, P Dobrynin GigaScience 9 (3), giaa005, 2020 | 78 | 2020 |
| Extended finite-state machine induction using SAT-solver VI Ulyantsev, FN Tsarev IFAC Proceedings Volumes 45 (6), 236-241, 2012 | 69 | 2012 |
| MetaFast: fast reference-free graph-based comparison of shotgun metagenomic data VI Ulyantsev, SV Kazakov, VB Dubinkina, AV Tyakht, DG Alexeev Bioinformatics 32 (18), 2760-2767, 2016 | 65 | 2016 |
| BFS-based symmetry breaking predicates for DFA identification V Ulyantsev, I Zakirzyanov, A Shalyto Language and Automata Theory and Applications: 9th International Conference …, 2015 | 46 | 2015 |
| Genome-wide sequence analyses of ethnic populations across Russia DV Zhernakova, V Brukhin, S Malov, TK Oleksyk, KP Koepfli, A Zhuk, ... Genomics 112 (1), 442-458, 2020 | 44 | 2020 |
| MetaCherchant: analyzing genomic context of antibiotic resistance genes in gut microbiota EI Olekhnovich, AT Vasilyev, VI Ulyantsev, ES Kostryukova, AV Tyakht Bioinformatics 34 (3), 434-444, 2018 | 41 | 2018 |
| Exact finite-state machine identification from scenarios and temporal properties V Ulyantsev, I Buzhinsky, A Shalyto International Journal on Software Tools for Technology Transfer 20 (1), 35-55, 2018 | 36 | 2018 |
| MuACOsm: a new mutation-based ant colony optimization algorithm for learning finite-state machines D Chivilikhin, V Ulyantsev Proceedings of the 15th annual conference on Genetic and evolutionary …, 2013 | 33 | 2013 |
| Hi-C metagenomics in the ICU: exploring clinically relevant features of gut microbiome in chronically critically ill patients V Ivanova, E Chernevskaya, P Vasiluev, A Ivanov, I Tolstoganov, ... Frontiers in microbiology 12, 770323, 2022 | 22 | 2022 |
| Efficient symmetry breaking for SAT-based minimum DFA inference I Zakirzyanov, A Morgado, A Ignatiev, V Ulyantsev, J Marques-Silva Language and Automata Theory and Applications: 13th International Conference …, 2019 | 22 | 2019 |
| Finding all minimum-size DFA consistent with given examples: SAT-based approach I Zakirzyanov, A Shalyto, V Ulyantsev Software Engineering and Formal Methods: SEFM 2017 Collocated Workshops …, 2018 | 21 | 2018 |
| Learning finite-state machines with ant colony optimization D Chivilikhin, V Ulyantsev International Conference on Swarm Intelligence, 268-275, 2012 | 21 | 2012 |
| Machine learning of phase transitions in nonlinear polariton lattices D Zvyagintseva, H Sigurdsson, VK Kozin, I Iorsh, IA Shelykh, V Ulyantsev, ... Communications Physics 5 (1), 8, 2022 | 20 | 2022 |
| Applying reinforcement learning and supervised learning techniques to play hearthstone I Kachalsky, I Zakirzyanov, V Ulyantsev 2017 16th IEEE International Conference on Machine Learning and Applications …, 2017 | 20 | 2017 |
| Evolutionary computation techniques for constructing SAT-based attacks in algebraic cryptanalysis A Pavlenko, A Semenov, V Ulyantsev Applications of Evolutionary Computation: 22nd International Conference …, 2019 | 19 | 2019 |
| Smart contract design meets state machine synthesis: Case studies D Suvorov, V Ulyantsev arXiv preprint arXiv:1906.02906, 2019 | 18 | 2019 |
| Evolutionary approach to coverage testing of IEC 61499 function block applications I Buzhinsky, V Ulyantsev, J Veijalainen, V Vyatkin 2015 IEEE 13th International Conference on Industrial Informatics (INDIN …, 2015 | 14 | 2015 |
| Combining exact and metaheuristic techniques for learning extended finite-state machines from test scenarios and temporal properties D Chivilikhin, V Ulyantsev, A Shalyto 2014 13th International Conference on Machine Learning and Applications, 350-355, 2014 | 13 | 2014 |
Daniil ChivilikhinSiemens Digital Industries SoftwareVerified email at siemens.com
