Publications

  • Daniil Berezun and Neil D. Jones
    Proceedings of the 2017 ACM SIGPLAN Workshop on Partial Evaluation and Program Manipulation,
  • Konstantin Zaitsev, Monika Bambouskova, Amanda Swain, Maxim N Artyomov
    Nature communications,
  • Berezun D.A.
    St. Petersburg State Polytechnical University Journal. Computer Science. Telecommunications and Control Systems,
  • Denis A. Mogilenko, Oleg Shpynov, Prabhakar Sairam Andhey, Laura Arthur, Amanda Swain, Ekaterina Esaulova, Simone Brioschi, Irina Shchukina, Martina Kerndl, Monika Bambouskova, Zhangting Yao, Anwesha Laha, Konstantin Zaitsev, Samantha Burdess, Susan Gillfilan, Sheila A. Stewart, Marco Colonna, Maxim N.Artyomov
    Immunity,
  • Shpilman A.A., Nadezhdina E.S.
    Computational Stochastic Modeling of Cellular Microtubule Network
    46th Annual Meeting of the American Society for Cell Biology,
  • Koznov, D., Pliskin, M.
    Computer-supported collaborative learning with mind-maps
    Communications in Computer and Information Science 17 CCIS, pp. 478-489,
  • Artem Trofimov
    In: Benczúr A. et al. (eds) New Trends in Databases and Information Systems. ADBIS 2018. Communications in Computer and Information Science, vol 909. Springer, Cham,
  • Ulyantsev V., Melnik M.
    Proceedings of International Conference on Algorithms for Computational Biology. - 2015. - 141-153,
  • Garanina N.O., Anureev I.S., Zyubin V.E
    Constructing verification-oriented domain-specific process ontologies
    System Informatics. Iss. 14. 2019. A.P. Ershov Institute of Informatics Systems, Siberian Branch of the Russian Academy of Sciences, Novosibirsk. P. 19–30.,
  • Igor Kuralenok, Natalia Starikova, Aleksandr Khvorov, and Julian Serdyuk

    The 27th ACM International Conference on Information and Knowledge Management (CIKM ’18), October 22–26, 2018, Torino, Italy. ACM, New York, NY, USA, 10 pages

  • Proceedings of the 2019 miniKanren and Relational Programming Workshop,
  • Egor Orachev, Ilya Epelbaum, Rustam Azimov, Semyon Grigorev

    Context-free path queries (CFPQ) extend the regular path queries (RPQ) by allowing context-free grammars to be used as constraints for paths. Algorithms for CFPQ are actively developed, but J. Kuijpers et al. have recently concluded, that existing algorithms are not performant enough to be used in real-world applications. Thus the development of new algorithms for CFPQ is justified. In this paper, we provide a new CFPQ algorithm which is based on such linear algebra operations as Kronecker product and transitive closure and handles grammars presented as recursive state machines. Thus, the proposed algorithm can be implemented by using high-performance libraries and modern parallel hardware. Moreover, it avoids grammar growth which provides the possibility for queries optimization.

    ADBIS 2020. Advances in Databases and Information Systems. Lecture Notes in Computer Science.,
  • Rustam Azimov, Semyon Grigorev
    GRADES-NDA '18 Proceedings of the 1st ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA),
  • Yuliya Susanina
    Context-free path querying (CFPQ) widely used for graph-structured data analysis in different areas. It is crucial to develop highly efficient algorithms for CFPQ since the size of the input data is typically large. We show how to reduce GFPQ evaluation to solving systems of matrix equations over R --- a problem for which there exist high-performance solutions. Also, we demonstrate the applicability of our approach to real-world data analysis.
    Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data,

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