Proceedings of 11th Moscow Conference on Computational Molecular Biology MCCMB'23

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Proceedings of 11th Moscow Conference on Computational Molecular Biology MCCMB'23

IITP RAS, 2023.

Regulatory potential of flipons revealed by deep learning.

Poptsova M., Умеренков Д., Fedorov A. et al., , in: Proceedings of 11th Moscow Conference on Computational Molecular Biology MCCMB'23.: IITP RAS, 2023.

Flipons – non-B DNA conformations – have been shown to play an important role in various genomic processes. Flipons identification and localization is difficult due to their dynamic nature. We developed deep learning approaches to identify non-B DNA secondary structures using available information from thousands of omics data sets. We created DeepZ models based on CNN and RNN, and ...

Added: November 30, 2023

Консервативные Z-флипоны и ассоциированные с ними омиксные факторы, в геномах мыши и человека.

Konovalov D., Beknazarov N., Герберт А. et al., В кн.: Proceedings of 11th Moscow Conference on Computational Molecular Biology MCCMB'23.: IITP RAS, 2023.

Разработанный нами ранее подход DeepZ [1], основанный на глубинных нейронных сетях и использующий как данные о последовательности, так и омиксные данные, был использован для генерации полногеномных аннотаций генома мыши и человека участками Z-ДНК. В данной работе мы использовали подход DeepZ для изучения консервативных Z-флипонов и консервативных транскрипционных факторов и гистоновых меток, которые обогащены Z-флипонами в обоих геномах. Мы отобрали более 500 ...

Added: December 1, 2023

Unsupervised domain adaptation methods for cross-species transfer of regulatory code signals

Pavel Latyshev, Fedor Pavlov, Herbert A. et al., , in: Proceedings of 11th Moscow Conference on Computational Molecular Biology MCCMB'23.: IITP RAS, 2023.

Added: December 1, 2023

Analysis of Cell Interactions between Tumour and Microenvironment

Mikhailova A., Poptsova M., Herbert A., , in: Proceedings of 11th Moscow Conference on Computational Molecular Biology MCCMB'23.: IITP RAS, 2023.

Added: December 1, 2023

Association of Z-RNA with QTL variants

Glimanova D., , in: Proceedings of 11th Moscow Conference on Computational Molecular Biology MCCMB'23.: IITP RAS, 2023.

Z-DNA and Z-RNA, or Z-flipons, have been shown to play an important role in many cellular processes. Recently the whole-genome map of Z-DNA was generated with Z-DNABERT based on transformer algorithm and trained on the experimental permanganate/S1 nuclease dataset [1]. It was demonstrated how predicted Z-flipons containing single nucleotide variants may affect Z-RNA formation and ...

Added: December 1, 2023

Глубинное обучение для выявления ассоциаций между функциональными геномными элементами

Цветкова А., В кн.: Proceedings of 11th Moscow Conference on Computational Molecular Biology MCCMB'23.: IITP RAS, 2023.

Архитектура глубинного обучения, трансформер, отличается механизмом внимания, который позволяет проинтерпретировать вывод моделей. DNABERT – одна из таких моделей, она обучена на геноме человека, то есть в ней уже заложена информация о некоторых взаимосвязях в ДНК. Модель можно настроить для других задач путем дообучения на небольшом датасете. В ходе работы была поставлена цель – проинтерпретировать мотивы, выявленные при ...

Added: December 1, 2023

Полигенная оценка риска с помощью моделей глубинного обучения

Perelygin V., Poptsova M., Камелин А. В. et al., В кн.: Proceedings of 11th Moscow Conference on Computational Molecular Biology MCCMB'23.: IITP RAS, 2023.

В данной работы было показано, что использование нелинейных моделей, в частности методов глубинного обучения, может заметно улучшить полигенную оценку риска некоторых видов заболеваний, в первую очередь высоко ассоциированных с эпистазом. ...

Added: December 1, 2023

High-throughput computational design of protein binders for complex targets using deep learning models

Alekseev K., Poptsova M., Shaitan A., , in: Proceedings of 11th Moscow Conference on Computational Molecular Biology MCCMB'23.: IITP RAS, 2023.

Computational protein design methods has transformed structural bioinformatics by overcom- ing many experimental limitations. Previously, experimental methods such as directed evo- lution were utilized to create protein binders. Many advancements in computational protein design have made it possible to generate de novo binders solely based on target structure and sequence information. However, despite recent progress, designing de novo protein ...

Added: December 1, 2023

Detection of non-coding variants in regulatory elements in patients with early atherosclerosis based on whole genome sequencing data

Okhrimenko G., Malko D., Zateyshchikov D. et al., , in: Proceedings of 11th Moscow Conference on Computational Molecular Biology MCCMB'23.: IITP RAS, 2023.

Added: December 1, 2023

Программный комплекс для предсказания функциональных элементов генома методами глубинного обучения с использованием омиксных данных

Voytetsky A., Fedorov A., Боровков П. В. et al., В кн.: Proceedings of 11th Moscow Conference on Computational Molecular Biology MCCMB'23.: IITP RAS, 2023.

Одной из важных задач геномики и молекулярной биологии состоит в предсказании расположения геномных функциональных элементов (ГФЭ), которые играют важную роль в работе и регуляции геномных и клеточных процессов, но для которых экспериментальные данных либо неполные, либо отсутствуют. Данная задача в настоящее время наиболее эффективно решается методами глубинного обучения на основе информации из доступных полногеномных экспериментов ...

Added: December 1, 2023

Biomarkers study to improve Machine Learning prediction of long-term risk of myocardial infarction, stroke, and cardiac death

K.M. Burkin, A.V. Kirdeev, Nikolaev K. Y. et al., , in: Proceedings of 11th Moscow Conference on Computational Molecular Biology MCCMB'23.: IITP RAS, 2023.

Added: December 1, 2023

Research target: Biology Computer Science Medical and Health Sciences

Language: English

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Proceedings of 11th Moscow Conference on Computational Molecular Biology MCCMB'23

Molecular dynamics simulations refine the pathogenicity of ACVRL1 kinase domain variants by quantifying impacts on ATP binding in pulmonary arterial hypertension

Borovikova I., Okhrimenko G., Zamyatin V. et al., Journal of Structural Biology 2026 Vol. 218 No. 2 Article 108315

Single amino acid substitutions in the ATP-binding domain of ACVRL1, a key receptor in the bone morphogenetic protein (BMP) signaling pathway, are frequently classified as variants of uncertain significance (VUS), complicating molecular diagnosis for pulmonary arterial hypertension (PAH) and Hereditary Hemorrhagic Telangiectasia (HHT). Since aberrant ATP binding disrupts downstream SMAD1/5/8 phosphorylation, we employed molecular dynamics ...

Added: May 20, 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 PapersVol. 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 ...

Added: May 19, 2026

uPAR deficiency triggers TGFβ1-mediated fibrotic remodeling in a cardiac perivascular-like microenvironment

Goltseva Y., Tsokolaeva Z., Beloglazova I. et al., Stem Cell Research and Therapy 2026 Vol. 17 No. 1

Background Cardiac fibrosis represents a significant health burden, with endothelial dysfunction and damaged perivascular microenvironment increasingly recognized as key contributors to fibrotic remodeling. The urokinase plasminogen activator receptor (uPAR), a critical component of the urokinase system, plays a pivotal role in vascular remodeling and fibrosis. While prior evidence indicates that uPAR deficiency leads to microvascular dysfunction and perivascular fibrosis, ...

Added: May 19, 2026

Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 3: System Demonstrations)

Association for Computational Linguistics, 2026.

Added: May 19, 2026

Dataset of solubility values for organic compounds in binary mixtures of solvents at various temperatures

Bezzubov S., Malikov D., Krasnov L. et al., Scientific data 2026 Vol. 13 Article 727

Solubility is a crucial property of organic compounds, impacting their potential applications in synthetic chemistry, materials science and drug design. Moreover, in technological processes mixtures of solvents are often utilized, making the solubility assessment more complicated. Predicting solubility values in mixtures of solvents from a molecular structure can help to address this issue, although a ...

Added: May 19, 2026

Aerokinesis: An IoT-Based Vision-Driven Gesture Control System for Quadcopter Navigation Using Deep Learning and ROS2

Pikalov V., Meshcheryakov V., Kondratev S. et al., Technologies 2026 Vol. 14 No. 1 P. 1–27

This paper presents Aerokinesis, an IoT-based software–hardware system for intuitive gesture-driven control of quadcopter unmanned aerial vehicles (UAVs), developed within the Robot Operating System 2 (ROS2) framework. The proposed system addresses the challenge of providing an accessible human–drone interaction interface for operators in scenarios where traditional remote controllers are impractical or unavailable. The architecture comprises ...

Added: May 19, 2026

Aerokinesis: An IoT-Based Vision-Driven Gesture Control System for Quadcopter Navigation Using Deep Learning and ROS2

Кондратьев С., Никитин Г. Э., Дырченкова Ю. А. et al., Technologies 2026 Vol. 14 No. 1 P. 1–27

Added: May 19, 2026

Применение методик кортикальной и субкортикальной стимуляции у пациентов с глиальными опухолями различной степени злокачественности доминантного по речи полушария головного мозга в условиях хирургии с пробуждением.

Андрушкевич О. М., Калиновский А. В., Гаврюшин А. В. et al., Нейрохирургия 2026 Т. 28 № 1 С. 33–42

Background. The application of cortical and subcortical stimulation during awake craniotomy mitigates the risk of persistent postoperative speech deficits. However, the functions of some white matter pathways remain inadequately understood, particularly the frontal aslant tract (FAT) of the dominant hemisphere. Aim. To evaluate the efficacy of cortical and subcortical stimulation techniques in the localization of glial tumors near ...

Added: May 18, 2026

Parallel Computational Technologies. PCT 2025

Springer, 2025.

This book constitutes the refereed proceedings of the 19th International Conference on Parallel Computational Technologies, PCT 2025, held in Moscow, Russia, during April 8–10, 2025. The 31 full papers included in this volume were carefully reviewed and selected from 122 submissions. These papers were organized under the following topical sections: High Performance Architectures, Tools and Technologies; ...

Added: May 18, 2026

KMHCR: A Key-Controlled Signal-Domain Transformation for 5G IoT Security

Ronglin Z., Wei L., Jiahong C. et al., Journal of Signal Processing Systems 2026 Vol. 98 P. 1–15

To address the need for lightweight and low-latency protection in massive resource-constrained 5G Internet of Things (IoT) systems, this paper proposes Key-Controlled Modulation Hopping and Constellation Rotation (KMHCR). KMHCR is designed as a physical-layer confidentiality-enhancement mechanism that avoids bit-wise full-payload encryption in the protection pipeline. It uses a shared key derived from channel-reciprocity secret key ...

Added: May 16, 2026

DPN Verifier: A Toolkit for Faster Soundness Verification and Repair of Process Models with Data

Suvorov N. M., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 3(2) P. 49–66

Data Petri Nets (DPNs) extend classical Petri nets to model processes where data directly influences control-flow, enabling a comprehensive view of system behavior and possibility to detect failure points that could otherwise be hidden. Soundness is a correctness criterion that captures such failure points as deadlocks and livelocks as well as model boundedness and absence ...

Added: May 16, 2026

QGKM: A Quantum Fidelity-Based Graph Clustering Framework for Robust Data Pattern Recognition in Education Social Networks QGKM: A Quantum Fidelity-Based Graph Clustering Framework for Robust Data Pattern Recognition in Education Social Networks

Neal N. X., Weiqing L., Dacheng H. et al., Algorithms 2026 Vol. 19 No. 5 P. 1–22

In the era of data-driven education, educational social networks generate large volumes of high-dimensional and complex-structured data through learner interactions, collaborative activities, and resource-sharing behaviors, posing significant challenges to traditional unsupervised learning methods. Such data often exhibit non-convex distributions, heterogeneity, and noise sensitivity, making conventional clustering approaches insufficient for capturing their intrinsic structural relationships. To ...

Added: May 13, 2026

Proceedings of the 9th Student Research Workshop associated with the International Conference Recent Advances in Natural Language Processing

Velichkov B., Nikolova-Koleva I., Slavcheva M., Shumen: INCOMA Ltd, 2025.

The RANLP 2025 Student Research Workshop (RANLPStud’2025) is a special track of the established international conference Recent Advances in Natural Language Processing (RANLP’2025). The RANLPStud is being organised for the 9th time and this year is running in parallel with the other tracks of the main RANLP 2025 conference. The target of RANLPStud’25 is to be a ...

Added: May 12, 2026

Biochemical Foundations of Emotion Regulation: Implications for Pharmacological and Psychological Interventions-A Narrative Review

Gerges M., Kosonogov V., OBM Neurobiology 2025 Vol. 9 No. 4 Article 310

Emotion regulation (ER) involves processes by which individuals modulate the intensity, duration, and expression of emotional responses, and its dysregulation is associated with a broad spectrum of psychological disorders. While traditionally conceptualized within psychological frameworks, ER is increasingly recognized as biologically grounded, involving intricate interactions between neurochemical, hormonal, and metabolic systems. This narrative review aims ...

Added: May 12, 2026

Интегрированная среда моделирования для верификации и валидации программ управления подключенными и высокоавтоматизированными транспортными средствами

Stepanyants V., Долгов И. М., Хорошилов Г. С. et al., Труды Института системного программирования РАН 2026 Т. 38 № 3 С. 95–110

Highly automated and connected vehicles are gradually entering the market. Currently, solutions are being proposed that allow these technologies to be used for cooperative driving automation, which can significantly improve traffic safety. Such technologies and their software should be tested to ensure safety before being implemented in real systems. Verification and validation of vehicular control ...

Added: May 12, 2026

Connected and Automated Vehicle Scenario Manager Graphical User Interface

Tikhonov R., Efendiev M. T., Fedotenkov A. A., 2026 International Russian Smart Industry Conference (SmartIndustryCon) 2026 P. 542–547

High-fidelity simulation environments like CARLA and ROS are essential for connected and automated vehicle research. They allow researchers to verify and validate new software and technology without the time, financial, and safety overheads of real-world testing. However, their operation requires considerable expertise for creating platform-specific scenario configuration files, which complicates the research workflow. This paper ...

Added: May 11, 2026

Proceedings 2026 IEEE 11th International Conference on Smart Cloud SmartCloud 2026 8-10 May 2026

Los Alamitos: IEEE Computer Society, 2026.

It is a great pleasure for us to welcome you on behalf of the conference committees, to the 11th IEEE International Conference on Smart Cloud (IEEE SmartCloud 2026), we are glad that we can have this international conference in New York city, USA. Now, please allow us to introduce the IEEE SmartCloud 2026 conference. The ...

Added: May 10, 2026

От неизвестности к прозрачности: обзор технологий объяснимого ИИ (XAI)

Avdoshin S. M., Pesotskaya E. Y., Информационные технологии 2026 Т. 32 № 4 С. 185–194

With the rapid advancement of artificial intelligence, and deep learning in particular, models have emerged that are capable of delivering highly accurate predictions. However, the internal logic of such models remains difficult to interpret—an issue of critical importance, especially in domains where the correctness of an algorithm directly affects high-stakes decision-making. One promising avenue for ...

Added: May 8, 2026

Explainable AI for Industry 5.0: Shedding light on the black box

Avdoshin S. M., Pesotskaya E. Y., Business Informatics 2026 Vol. 20 No. 1 P. 7–28

The rapid development of artificial intelligence (AI) is accompanied by increasing computational complexity and decreasing model transparency, which significantly limits its adoption in critical domains that require a high level of trust, interpretability, and justification of decisions. Under these conditions, the field of Explainable Artificial Intelligence (XAI) has gained particular importance as it focuses on approaches and technologies that ...

Added: May 8, 2026

Comparative Analysis of Students’ Perceptions of Programming Puzzles: Parson’s and Wordle-Like

Varnavsky A., IEEE Access 2026 Vol. 14 P. 37487–37508

Puzzles are an excellent tool for learning computer science and programming, fostering increased interest, engagement, and motivation among students, as well as developing logical, critical, and computational thinking. Among beginner programmers, Parson's Programming Puzzles are quite popular, aimed at mastering the basic syntactic and logical constructs of programming languages. However, as students' skills grow, their ...

Added: May 7, 2026

Towards performance analysis of GPU-aware MPI over Angara interconnect

Ismagilov T., Mukosey A., Smirnov F. et al., International Journal of High Performance Computing Applications 2026 Vol. 40 No. 2 P. 240–253

One of the most important aspects of supercomputer development in the post-Moore era is the interconnect technologies that allow one to unite a multitude of processing elements into a well-synchronized computing system. Novel types of supercomputer interconnect require careful benchmarking and compliance with the requirements of modern hardware trends. GPU-based heterogeneous computing is one of ...

Added: May 7, 2026

Multimodal graph, surface, and language-based model for protein protein interaction prediction

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

Prediction of protein-protein interactions using point transformer and spherical Convex Hull graphs

David Arteaga, Poptsova M., Computational and Structural Biotechnology Journal 2026 Vol. 31 P. 82–93

Accurate predictions and large-scale identification of protein-protein interactions (PPIs) are crucial for understanding their inherent biological mechanisms and protein functions in virtually all biological processes. Nowadays, graph-based deep learning models have made significant contributions in modeling proteins with physicochemical and geometric features. However, most of these models rely on conventional graph construction methods, such as ...

Added: December 22, 2025