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  • ИНСТИТУТ БИОИНФОРМАТИКИ. СБОРНИК ТЕЗИСОВ 2020/21
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News
June 5, 2026
Neural Network Maps as a Method for Constructing Mathematical Models
Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
June 5, 2026
‘In the Age of Technology, It Is Interesting to Look into the Past and Think about What We Can Take from It
Polina Tabakova decided to apply for a Philology degree at HSE in Nizhny Novgorod because she grew up in Mari El and did not want to move far away from the Russian forests. In an interview for the Young Scientists of HSE University project, she spoke about the genre of the campus novel, the existential drama of Kolobok, and a blackout version of Eugene Onegin.
June 5, 2026
HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.

 

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ИНСТИТУТ БИОИНФОРМАТИКИ. СБОРНИК ТЕЗИСОВ 2020/21

СПб. : Федеральное государственное автономное образовательное учреждение высшего образования "Санкт-Петербургский политехнический университет Петра Великого", 2021.

Bioinformatics Institute 2020/21. Project abstracts. Bioinformatics Summer School 2021. Abstracts.

Chapters
IMPROVE CASUAL GENE PRIORITIZATION BY PATIENT,S PHENOTYPE. IDENTIFICATION AND PARSING OF RELEVANT MENDELIAN DISEASE ARTICLES
Konstantinovskiy N., Smirnov D., Holger P., , in: ИНСТИТУТ БИОИНФОРМАТИКИ. СБОРНИК ТЕЗИСОВ 2020/21.: St. Petersburg: Федеральное государственное автономное образовательное учреждение высшего образования "Санкт-Петербургский политехнический университет Петра Великого", 2021. P. 24–24.
Added: August 9, 2021
AGE-RELATED CHANGES IN METHYLATION PATTERNS AT SITES OF ACTIVE HUMAN DNA REPLICATION
Konstantinovskiy N., Kirillova E., Cherniatchik R., , in: ИНСТИТУТ БИОИНФОРМАТИКИ. СБОРНИК ТЕЗИСОВ 2020/21.: St. Petersburg: Федеральное государственное автономное образовательное учреждение высшего образования "Санкт-Петербургский политехнический университет Петра Великого", 2021. P. 59–60.
Added: August 9, 2021
Research target: Biology Computer Science
Priority areas: IT and mathematics
Language: English
Keywords: bioinformaticsбиоинформатикавычислительная геномикаcomputational genomics
ИНСТИТУТ БИОИНФОРМАТИКИ. СБОРНИК ТЕЗИСОВ 2020/21
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Proceedings of the 43rd International Conference on Machine Learning (ICML 2026)
Seul: PMLR, 2026.
Added: June 4, 2026
Adaptive glucose homeostasis in the desert rodent Acomys cahirinus: high glucose tolerance, liver metabolic shifts, and visceral adiposity
Boldyreva M., Mohammad R., Agareva M. et al., FRONTIERS IN ANIMAL SCIENCE 2026 Vol. 7 Article 1837838
Mammals from arid ecosystems face distinct physiological challenges: water scarcity and unpredictable food availability require the integration of energy storage, maintenance of water balance, and flexible switching between nutrients. Our previous study demonstrated lower fasting blood glucose levels in the desert rodent Acomys cahirinus (African spiny mouse), which also possesses a unique regenerative ability. The aim of ...
Added: June 3, 2026
OpenAtom Foundation. Консорциум, развивающий Open Source в Китае.
Silakov D., Системный администратор 2026 № 3 С. 28–33
В статье про платформы для разработки открытого ПО в Китае мы рассказали про GitCode – молодой проект, позиционируемый как площадка для разработчиков со всего мира. Сейчас на GitCode размещаются проекты, созданные в КНР, но некоторые из них уже известны и на международной арене. Помочь открытым проектам в становлении, развитии и расширению аудитории призван фонд OpenAtom ...
Added: June 2, 2026
The recognition-by-components method
Slivnitsin P., Mylnikov L., Engineering Applications of Artificial Intelligence 2026 Vol. 179 Article 115185
The paper describes a applied artificial intelligence task of recognition-by-components method of real objects based on the recognition of a limited set of primitives or components. The recognition-by-components makes it possible to determine the components, that compose an object, and increase the number of recognizable objects without degrading the recognition quality. Training is performed on ...
Added: May 29, 2026
ИССЛЕДОВАНИЕ АССОЦИАЦИИ ГЕНЕТИЧЕСКИХ ВАРИАНТОВ С РАЗВИТИЕМ МУЗЫКАЛЬНЫХ СПОСОБНОСТЕЙ ЧЕЛОВЕКА
Kazantseva A. V., A.V. Toropova, Khusnutdinova E. K. et al., ВАВИЛОВСКИЙ ЖУРНАЛ ГЕНЕТИКИ И СЕЛЕКЦИИ, Федеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наук» (ИЦиГ СО РАН) (Новосибирск) 2025 Vol. 30 No. 3 P. 470–481
The development of musical abilities, including absolute pitch, musical memory, rhythm sense, and musicality, at a high degree is determined by a hereditary component (up to 68 %). The studies implementing a genome-wide linkage and association approach to musical aptitude have revealed more than 100 genetic loci. This spectrum is comprised of the genes encoding ...
Added: May 29, 2026
Brain-Computer Interfaces for Gait Rehabilitation After Stroke A Scoping Review
Mokienko O., Zisman M. A., Bobrov P. et al., American Journal of Physical Medicine and Rehabilitation 2026 Vol. 105 No. 6 P. 555–563
Brain-computer interfaces (BCIs) represent a promising technology for restoring lower limb motor functions and gait after stroke. The application of BCIs in this field is supported by a limited number of studies. The objective of the review was to systematically and critically evaluate the current evidence on the use of BCIs for lower limb function ...
Added: May 28, 2026
Generalizing the Brady-Yong Algorithm: Efficient Fast Hough Transform for Arbitrary Image Sizes
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The Hough (discrete Radon) transform (HT/DRT) is a digital image processing tool that has become indispensable in many application areas, ranging from general image processing to neural networks and X-ray computed tomography. The utilization of the HT in applied problems demands its computational efficiency and increased accuracy. The de facto standard algorithm for the fast ...
Added: May 28, 2026
Universal Comparison Methodology for Hough Transform Approaches
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Added: May 28, 2026
Sweet-taste liking is associated with preference for less risky and immediate rewards in economic decision-making
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Background:  Delay discounting refers to the tendency to choose sooner, smaller rewards over larger, later rewards. Many previous studies link this tendency positively to reward sensitivity, yet the specific mechanisms behind this association remain poorly understood. Reward sensitivity may relate to delay discounting through at least three possible pathways: increased sensitivity to reward size, increased sensitivity ...
Added: May 27, 2026
ИНФОРМАЦИОННЫЕ ТЕХНОЛОГИИ И ТЕХНИЧЕСКИЕ СРЕДСТВА УПРАВЛЕНИЯ (ICCT-2024)
М.: Институт проблем управления им. В.А. Трапезникова РАН, 2024.
В сборник вошли материалы VIII Международной научной конференции «Информационные технологии и технические средства управления» (ICCT-2024). На конференции были рассмотрены вопросы, касающиеся перспектив развития научного приборостроения в телекоммуникационных и управляющих системах, биомедицинской информатики, аппаратного и программного обеспечения информационнокоммуникационных систем, надежности, диагностики и неразрушающего контроля, систем управления и автоматизации, цифровых экосистем, управления производством и логистикой, методов математического ...
Added: May 27, 2026
Non-linear in-band interference cancellation on base of conjugate gradients method
Degtyarev A., Bakhurin S., Yudin N., DSPA 2026 P. 1–6
This paper investigates one possible solution to the problem of self-interference cancellation (SIC) arising in the design of in-band full-duplex (IBFD) communication systems. Self-interference cancellation is performed in the digital domain using multilayer nonlinear models adapted via gradient-based optimization. The presence of local minima and saddle points during the adaptation of multilayer models limits the ...
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28th European Conference on Artificial Intelligence, 25-30 October 2025, Bologna, Italy – Including 14th Conference on Prestigious Applications of Intelligent Systems (PAIS 2025)
IOS Press, 2025.
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Comparative Study of Training Methods and Architectures of Echo State Networks
Androsov I., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 3 P. 87–114
This paper examines echo state networks (ESNs), one of the most prevalent approaches to implementing reservoir computing. An ESN consists of a recurrent neural network with fixed (untrained) weights and a readout layer that is typically linear and trainable. This approach enables the creation of energyefficient and computationally efficient neural networks capable of real-time learning. However, since ...
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Novelty, Category and Orientation Tuning for Printed Characters: A Magnetoencephalography Study with Fast Periodic Visual Stimulation
Kochetkova E., Kostanian D., Martynova O. et al., Brain Topography 2026 Vol. 39 No. 4 Article 51
Letter recognition is assumed to involve several levels of analysis, including coarse tuning for category and novelty and more fine tuning for specific features, related to letter orientation. We employed an oddball fast periodic visual stimulation (FPVS) paradigm with magnetoencephalography (Elekta VectorView, 306 sensors) to study neural discrimination responses in the source space. Using contrasts ...
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Рефакторинг исходного кода на основе LLM и расширения UML
Караваева Е. А., Кулигин Л. А., Rezunik L. et al., Труды Института системного программирования РАН 2026 Т. 38 № 3 С. 67–94
В статье представлен метод рефакторинга исходного кода на основе интеграции большой языковой модели (LLM) и расширенной UML-модели программного кода. Предложенный подход позволяет выявлять проблемные участки кода с использованием функций тревожности и структурных метрик классов, а затем выполнять автоматизированный рефакторинг. Ключевой особенностью метода является использование LLM для генерации формальных спецификаций на языке OCL (Object Constraint Language), ...
Added: May 24, 2026
Coping with AI errors with provable guarantees
Tyukin I., Tyukina T., van Helden D. P. et al., Information Sciences 2024 Vol. 678 Article 120856
AI errors pose a significant challenge, hindering real-world applications. This work introduces a novel approach to cope with AI errors using weakly supervised error correctors that guarantee a specific level of error reduction. Our correctors have low computational cost and can be used to decide whether to abstain from making an unsafe classification. We provide ...
Added: May 23, 2026
Overcoming the Curse of Dimensionality with Synolitic AI
Zaikin A., Sviridov I., Sosedka A. et al., Technologies 2026 Vol. 14 No. 2 Article 84
High-dimensional tabular data are common in biomedical and clinical research, yet conventional machine learning methods often struggle in such settings due to data scarcity, feature redundancy, and limited generalization. In this study, we systematically evaluate Synolitic Graph Neural Networks (SGNNs), a framework that transforms high-dimensional samples into sample-specific graphs by training ensembles of low-dimensional pairwise ...
Added: May 23, 2026
Stable On-the-Fly Learning for Dynamic Neural Networks With Delayed Inputs
Chertopolokhov V., Mukhamedov A., Bugriy G. et al., IEEE Access 2026 Vol. 14 P. 14369–14392
This study presents on-the-fly identification and multi-step prediction of nonlinear systems with delayed inputs using a dynamic neural network combined with a smooth projection onto ellipsoids. The projection enforces parameter constraints that guarantee stability, while a Lyapunov–Krasovskii analysis yields computable ultimate error bounds. Riccati-type matrix inequalities are derived, providing an efficient vectorization–projection–devectorization implementation suitable for ...
Added: May 22, 2026
ML-based Fast Simulation of FARICH Responses
Shipilov F., Barnyakov A., Ivanov A. et al., / Series Physics "arxiv.org". 2026.
A fast simulation of the detector response is a vital task in high-energy physics (HEP). Traditional Monte-Carlo methods form the backbone of modern particle physics simulation software but are computationally expensive. We present a machine-learning-based approach to fast simulation of the Focusing Aerogel Ring Imaging Cherenkov (FARICH) detector response. Given a particle track and momentum, ...
Added: May 19, 2026
Optimizing Computational Infrastructure for Large Language Models in Bioinformatics: A Case Study
Beknazarov N., , in: Parallel Computational Technologies, 19th International Conference, PCT 2025, Moscow, Russia, April 8–10, 2025, Revised Selected Papers. (CCIS, volume 2891)Vol. 2891.: Springer, 2026. P. 3–16.
This paper addresses the challenge of efficiently training Large Language Models (LLMs) on large-scale, sparse omics datasets in high-performance computing (HPC) environments. Using over 1000 BED tracks as a representative data source, we propose a method combining interval-based chunked storage, sparse matrix transformation, and parallel data loading, integrated within a PyTorch Lightning training framework. Our ...
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Natural hazard database from Internet publications: text mining with a large language model
Derkacheva A., Sakirkina M., Kraev G. et al., /. 2026.
Comprehensive data on natural hazards and their consequences are crucial for effective for risk assessment, adaptation planning, and emergency response. However, many countries face challenges with fragmented, inconsistent, and inaccessible data, particularly regarding local-scale events. To address this data gap in Russia, we developed an end-to-end processing pipeline that scrapes news from various online sources, ...
Added: April 28, 2026
Algorithmic overlaps as thermodynamic variables: from local to cluster Monte Carlo dynamics in critical phenomena
Pilé I., Deng Y., Shchur L., / Series arXiv "math". 2026. No. 2604.10254.
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Gabdullin N., Androsov I., / Series Computer Science "arxiv.org". 2026.
Label prediction in neural networks (NNs) has O(n) complexity proportional to the number of classes. This holds true for classification using fully connected layers and cosine similarity with some set of class prototypes. In this paper we show that if NN latent space (LS) geometry is known and possesses specific properties, label prediction complexity can ...
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Arteaga Moreano B. D., Chervov N., Poptsova M., Scientific Reports 2026 Vol. 16 No. 1 Article 4772
Accurate prediction of protein-protein interactions (PPIs) is fundamental to understanding biological processes and disease mechanisms. While deep learning offers a powerful alternative to costly experimental methods, existing approaches often overlook critical protein-surface information and rely on simplistic feature fusion techniques, thereby limiting performance. To address this, we introduce GSMFormer-PPI, a novel multimodal framework that integrates ...
Added: February 4, 2026
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