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Information × Registration Number 0225U002260, (0120U101734) , R & D reports Title Development and application of data research methods, machine learning and artificial intelligence algorithms in complex systems of fundamental and applied physics, biology, economics, and environment. popup.stage_title Розробка та застосування методів дослідження даних, алгоритмів машинного навчання та штучного інтелекту в складних системах в фундаментальній і прикладній фізиці, біології, економіці та навколишньому середовищі Head Kordyuk Oleksandr A., Доктор фізико-математичних наук Registration Date 26-02-2025 Organization State Research Institution "Kyiv Acedimic University" popup.description1 The purpose of the work is to develop data science methods and conduct interdisciplinary research aimed at the development and application of machine learning and artificial intelligence methods, including cloud services, based on methods of processing large data sets to a wide range of scientific and practical tasks in various fields of knowledge. Particularly, to the tasks, which arise from environmental research in the field of bioinformatics and biomedicine, materials physics, high energy physics, process optimization in economics and expert decision-making as well as research on innovation activities. popup.description2 The goal is to develop and mathematically substantiate computer modeling and machine learning methods applied to various scientific and practical interdisciplinary tasks in the field of bioinformatics and systems biology, high-energy astrophysics and cosmology, physical materials science, environmental research, and the development of innovative approaches to digital science. In the process of performing scientific work: new machine learning and computer modeling algorithms based on new approaches to ranking problems, numerical differentiation of functions of several variables, and methods for classifying data using diffusion mappings were developed and mathematically substantiated; a specialized relational database IGEA was created, which combines gene expression profiles and metadata in placental samples from different stages of pregnancy under normal and pathological conditions; a high-resolution global metagenomic atlas of the microbiome inhabiting urban public transport networks was built; an algorithm for reconstructing sequencing sequences from the de Bruyne counting graph has been created, which allows storing large arrays of metagenomic data, which supports a number of sequence search queries; methods for applying quantum computing and quantum machine learning in bioinformatics have been developed, in particular for DNA sequence alignment problems; a number of software modules have been developed for the MMODA cloud platform for multichannel astronomy data processing; based on the X-ray properties of sources in the Seyfert galaxy class, promising objects for searching for a neutrino signal have been identified; a new mathematical tool has been proposed for assessing the similarity of large-scale structures of simulated Universes with different values ​​of the cosmological parameter, which describes the current mean-square fluctuation of matter, which is averaged over a sphere with a radius of 8 Mpc; the evolution of Betti curves obtained using persistent-h Product Description popup.authors Bezhuba Volodymyr V. Savchenko Denys O. Semenov Vasyl Yu. Semenova Yevheniia V. Solodkyi Serhii H. Tymchyshyn Vitalii B. Feia Oleh D. Frolova Alina O. Shadura Vitalii M. Yakymenko Danylo Yu. popup.nrat_date 2025-02-26 Close