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Программный комплекс для предсказания функциональных элементов генома методами глубинного обучения с использованием омиксных данных
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In book
IITP RAS, 2023.
Krasnov L., Malikov D., Kiseleva M. et al., Journal of Medicinal Chemistry 2026 Vol. 69 No. 8 P. 8838–8851
In this work, we developed a straightforward data-driven approach to predict the cytotoxicity of metal complexes based entirely on their (metal + ligands) composition. To this end, we have manually curated MetalCytoToxDB─a comprehensive experimental database comprising 26,500 IC50 values for 7050 metal complexes against 754 cell lines from 1921 articles. Based on these, machine learning ...
Added: April 23, 2026
Ершов И. А., Системная инженерия и инфокоммуникации 2025 № 4 С. 11–14
The heat consumption of residential buildings is a stochastic series. It is necessary for the design of thermal energy regulators the creation of a neural network model. In the paper, the model is carried out based on Long Short-Term Memory (LSTM). The high accuracy of reproducing the series was achieved by training the model on ...
Added: April 22, 2026
Makarov D. M., Kalikin N., Gurikov P. et al., Journal of Supercritical Fluids 2026 Vol. 235 Article 106979
Supercritical CO2 (scCO2 ) is an environmentally friendly solvent, but its low polarity limits the solubility of polar compounds. Cosolvents are commonly used to enhance solvation capability, yet comprehensive datadriven studies are scarce. We compiled the largest dataset to date — 4401 experimental solubility records with 22 cosolvents for 93 nonionic solutes, plus 4855 records ...
Added: April 19, 2026
Lysenok N., Фундаментальная и прикладная математика 2026 Т. 26 № 3 С. 33–42
This study examines the impact of realized volatility forecasts on the performance of active trading strategies in the Russian equity market. Using a sample of 17 liquid stocks over the period 2014–2026, a hybrid forecasting model is developed that combines HAR-J with gradient boosting; its superiority over the baseline HAR-J specification is confirmed by the ...
Added: April 17, 2026
Plesovskikh A. E., Journal of Applied Economic Research 2023 Т. 22 № 2 С. 323–354
Modern studies widely discuss the role of special economic zones in stimulating the economic growth and development of Russia, generating the necessary investment flows and increasing the country's innovative potential by expanding production in high-tech sectors of the economy with high added value. The purpose of the study is to model the process of generating ...
Added: April 13, 2026
Опыт генерации оценок эмоциональной валентности и возбуждения слов на основе символьно-уровневой CNN
Lyusin D., Валуева Е. А., Sysoeva T., В кн.: Психология познания: Материалы Всероссийской научной конференции, ЯрГУ, Институт психологии РАН, 5–6 декабря 2025 г.: Институт психологии РАН, 2026. С. 310–314.
Эмоциональная окраска слов широко используются в различных академических и прикладных исследованиях, от анализа текстов до понимания когнитивных процессов. Актуальной задачей является создание объёмных датасетов с оценками слов по ряду эмоциональных параметров. Современные методы машинного обучения, основанные на семантической близости слов, извлекаемой из текстовых корпусов, демонстрируют высокие корреляции с человеческими оценками, однако иногда наблюдаются существенные расхождения. ...
Added: April 10, 2026
Fedorov A., Вакку Г. В., Лебедева С. Э., Галактика медиа: журнал медиа исследований 2026 Т. 8 № 2 С. 163–182
With the increasing volume of data, university faculty may spend years processing and organizing information. Personalized assistance, content recommendations, data collection for literature reviews, and bibliographic citation formatting reinforce the role of artificial intelligence and neural network tools for scholarly communication. This paper discusses practical examples of using tools such as Elicit, SciSpace, Consensus, Undermind, ...
Added: April 7, 2026
Efremov A., Portnoy S., Волошин А. Д., Первая миля 2025 № 8 С. 20–28
Выполнен комплексный обзор методов машинного обучения (ML), применяемых для повышения устойчивости сигнала к помехам в каналах связи. Бурное развитие поколений беспроводной связи, активная разработка концепции 6G предъявляют высокие требования к задержке, скорости и надежности передачи данных. Традиционные подходы к защите от помех, основанные на строгих аналитических моделях, зачастую не справляются с хаотичной природой плотных гетерогенных ...
Added: April 4, 2026
Pakshin P., Legal Issues in the Digital Age 2026 Vol. 7 No. 1 P. 32–48
Artificial intelligence plays a significant role in automation, minimizing human intervention in fields such as medicine, art, and law. Despite the historically close relationship between art and technology, generative AI has expanded the potential for creative activity. A significant catalyst for this process has been the proliferation of pre-trained AI systems, which have accelerated the ...
Added: March 31, 2026
Yusupov V., Sukhorukov N., Frolov E., User Modelling and User-Adapted Interaction 2026 Vol. 36 Article 2
Graph-based recommender systems have emerged as a powerful paradigm for personalized recommendations. However, their reliance on full model retraining to incorporate new users or new interactions creates scalability barriers. The task becomes infeasible in real-life recommender systems due to excessive time and resource costs involved. To address this limitation, we propose a fast and efficient ...
Added: March 15, 2026
Yusupov V., Sukhorukov N., Frolov E., User Modeling and User-Adapted Interaction 2025 P. 1–24
Graph-based recommender systems have emerged as a powerful paradigm for personalized recommendations. However, their reliance on full model retraining to incorporate new users or new interactions creates scalability barriers. The task becomes infeasible in real-life recommender systems due to excessive time and resource costs involved. To address this limitation, we propose a fast and efficient ...
Added: March 14, 2026
Maltseva S. V., Бериков В. Б., Кладов Д. Е. et al., В кн.: Информатика и прикладная математика: Материалы X Международной научно-практической конференции (08.10 - 11.10.2025 г.)Т. 1: Сборник материалов часть 1.: Алматы: Институт информационных и вычислительных технологий КН МНВО РК, 2025. С. 227–232.
This paper examines the problem of clustering consumption patterns for a private household. An ensemble algorithm based on the Wasserstein metric was developed and applied to cluster daily load profiles. The proposed approach allows for identifying typical energy consumption scenarios and interpreting consumer behavior. Results from computational experiments using real data are presented. ...
Added: March 3, 2026
Moshkin A., Лапутин Ф. А., Сидоров И. В., DIGITAL DIAGNOSTICS 2024 Т. 5 № S1 С. 40–42
BACKGROUND: Ovarian reserve reflects a woman's ability to successfully realize reproductive function. The assessment of ovarian reserve is an urgent task for clinical practice [1] and is important in scientific research. The use of computerized diagnostic image processing methods can accelerate and facilitate the performance of routine tasks in clinical practice. Their use in retrospective ...
Added: February 21, 2026
Кузнецов В. А., Yasnitsky L., В кн.: Искусственный интеллект в решении актуальных социальных и экономических проблем ХХI века : Сборник статей по материалам Десятой всероссийской научно-практической конференции с международным участием (г. Пермь, ПГНИУ, 9–10 октября 2025 г.).: Пермский государственный национальный исследовательский университет, 2025. С. 240–247.
В работе представлены разработка и сравнительный анализ методов машинного обучения для задачи бинарной классификации пациентов с риском развития церебрального
инсульта. Исследовательский процесс включал этап тщательного разведочного анализа
данных, за которым последовала реализация и оценка трех моделей: дерева решений,
случайного леса и нейронной сети. Целью работы является определение наиболее эффективного алгоритма для построения системы поддержки врачебных решений, способной своевременно ...
Added: February 15, 2026
Suvorova A., В кн.: XXII национальная конференция по искусственному интеллекту с международным участием (КИИ-2025)Т. 1.: СПб.: Санкт-Петербургский Федеральный исследовательский центр РАН, 2025. С. 310–318.
В работе исследуется проблема чрезмерного полагания (overreliance) пользователей на результаты интерпретации моделей машинного обучения, а также способов ее решения с помощью пояснений, генерируемых большими языковыми моделями (LLM). Результаты эксперимента показали, что большинство моделей, так же как и пользователи-люди в исходном эксперименте, игнорировали аномалии или предлагали правдоподобные, но ложные объяснения, рационализируя выводы. Это указывает на риски ...
Added: February 15, 2026
Shchepeleva M., Столбов М. И., Экономика и математические методы 2026 Т. 62 № 1 С. 63–77
Predicting bank defaults is an important task for the entire economy. Early identification of troubled banks helps to prevent impending bank failures or minimize the losses associated with them. The paper discusses the state of the art of instrumental methods and data used for this purpose. The theoretical background, the evolution of methodological approaches used ...
Added: February 13, 2026
Morychev G., Sizykh D., Sizykh N., IEEE Access 2025 Vol. 13 P. 213194–213210
One of the main tools for analyzing large volumes of financial data is the use of clustering methods and models, which allow the identification of various patterns. This study examines the problem of clustering time series that reflect the behavior of prices, yields, modes, trends, and a number of related stock indicators. The relevance and ...
Added: February 3, 2026
Yusupov V., Sukhorukov N., Frolov E., , in: User Modeling and User-Adapted Interaction.: Springer, 2026. Ch. 36.2 P. 1–24.
Graph-based recommender systems have emerged as a powerful paradigm for personalized recommendations. However, their reliance on full model retraining to incorporate new users or new interactions creates scalability barriers. The task becomes infeasible in real-life recommender systems due to excessive time and resource costs involved. To address this limitation, we propose a fast and efficient ...
Added: January 29, 2026
Laurinavichyute A., Lopukhina A., Reich D., , in: Proceedings of the 63rd Annual Meeting of the Association for Computational LinguisticsVol. 2: Short papers.: Wien: Association for Computational Linguistics, 2025. P. 59–66.
Dyslexia, a common learning disability, requires an early diagnosis. However, current screening tests are very time- and resourceconsuming. We present an LSTM that aims to automatically classify dyslexia based on eye movements recorded during natural reading combined with basic demographic information and linguistic features. The proposed model reaches an AUC of 0.93 and outperforms the ...
Added: January 19, 2026
Lysenok N., Фундаментальная и прикладная математика 2025 Т. 25 № 4 С. 90–107
The aim of the study is to assess to what extent modern machine learning methods can improve the accuracy of forecasting the volatility of Russian stocks and whether such improvements lead to real advantages when applied in investment strategies. The work combines a review of theoretical approaches to volatility analysis with empirical research based on ...
Added: January 16, 2026