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

Methodological limitations of the BrainStructureAges pipeline from the volBrain platform: a brief report of the normative pediatric group

Korotkova E., Kulikova S., Lvova O. et al., Pediatric Radiology 2026 P. 1–9

Background Predicted brain age is a widely used neuroimaging biomarker of brain maturation. However, limited normative pediatric datasets in model training raise concerns about systematic biases when applied to children. This study evaluates the hypothesis of predicted brain age overestimation in typically developing pediatric populations. Objective To analyze predicted brain age and brain delta in a large, age- ...

Added: October 3, 2026

On Practical Aspects of Constructing Quasi-Cyclic Subfield Subcodes of Dual Elliptic Codes and Their Application in McEliece-type Cryptosystems

Kuninets A., IEEE Transactions on Information Theory 2026 P. 1–1

In this work we study the applicability of Quasi-Cyclic Subfield Subcodes of Dual Elliptic (QC-SSDE) codes for integration into code-based cryptographic schemes. Detailed algorithms are provided for constructing parity-check matrices as well as block-circulant parity-check matrices for this family of codes, accompanied by empirical results that enable the construction of QC-SSDE codes with predetermined dimensions. ...

Added: October 3, 2026

Инкрементальный метод обновления многомерного куба по неупорядоченному потоку событий журналов информационных систем

Zykov S. V., Уфимцев Г. А., Моделирование, оптимизация и информационные технологии 2026 Т. 14 № 8 С. 1–13

Информационные системы формируют большие объёмы событийных журналов, которые используются для анализа работы приложений и сервисов. При этом события могут поступать в аналитический контур позже момента их фактического возникновения и не в исходном порядке. Такая рассинхронизация приводит к ошибкам при построении агрегированных временных показателей, а регулярный полный пересчёт многомерного аналитического куба требует значительных вычислительных затрат. Целью ...

Added: October 2, 2026

Polarization of opinions in the group: a modeling algorithm considering the dynamics of social bonds

Chebotarev V., Andreyuk D., Elizarova Anastasiya et al., Procedia Computer Science 2022 Vol. 213 No. C P. 596–601

The dynamics of opinion in a group are of interest for a number of practical purposes. In particular, consensus helps and polarization of opinions hinders cohesive teamwork. Existing approaches for modeling opinion dynamics mostly do not take into account the dynamism of social relations in a group. This paper proposes an algorithm and a program ...

Added: October 2, 2026

Enhancing Boundary Stability in Decision Trees and Random Forests: A Weighted Sample Duplication Approach

Konstantinov A., Elizarova Anastasiya P., Utkin L., Computing, Telecommunications and Control 2026 Vol. 19 No. 1 P. 16–25

Decision trees and their ensemble extensions, such as random forests, are widely used as classification models due to their simplicity and interpretability. However, in many real-world tasks where class labels overlap in the feature space, standard decision trees rely on hard splits that create fragile decision boundaries. In these regions, small perturbations in the input ...

Added: October 2, 2026

HLA class I escape drives the evolution of SARS-CoV-2 in human populations

Ekaterina D. Riumina, Klink G. V., Alekseeva E. et al., PNAS, США 2026 Vol. 123 No. 35 P. 1–20

The role of escape from the cytotoxic T cell (CTL) response in SARS-CoV-2 evolution remains controversial. Here, we study the origin and spread of SARS-CoV-2 variants whose mutations reduce presentation by the HLA class I alleles common in human populations. We find that 35% of mutations that are characteristic of the variants of concern, and ...

Added: October 2, 2026

Bayesian Adaptive Sparse Copula

Prokhorov A., Burda M., Journal of Computational and Graphical Statistics 2026 P. 1–13

Bayesian nonparametric density estimation procedures are typically based on single-scale priors, such as Dirichlet process mixtures. Alternative multiscale density priors built on decision trees have many well-known advantages, including the ability to characterize abrupt local changes and to provide an estimate with a desired level of resolution. Despite their theoretical appeal, multiscale methods have typically ...

Added: October 2, 2026

Pericyte-derived cancer-associated fibroblasts correlate with poor survival and are enriched after chemoradiotherapy in glioblastoma

Aly Ismailov, Poptsova M., Plos One 2026 Vol. 21 No. 9 Article e0355902

Added: October 2, 2026

Консервативные энтропийно и энергетически корректные разностные методы для одномерных квазигазодинамических систем уравнений

Zlotnik A., Математические заметки 2026 Т. 120 № 6 С. 1005–1009

Численным методам решения систем газодинамических уравнений посвящена обширная литература. Ранее было разработано и успешно апробировано специальное семейство симметричных по пространству консервативных разностных методов, основанных на предварительной кинетической, точнее, квазигазодинамической (КГД), регуляризации этих уравнений. Актуальной задачей является построение численных методов, которые обладают не только свойством консервативности по массе, импульсу и полной энергии, но и удовлетворяют условиям энтропийной ...

Added: October 1, 2026

Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence (IJCAI 2026)

International Joint Conferences on Artificial Intelligence, 2026.

Added: October 1, 2026

Ensemble-based Prototype-Augmented Multimodal Fusion for Ambivalence/Hesitancy Recognition

Ryumina E., Aksenov A., Сысоев Д. С. et al., IEEE Computer Society, 2026.

Ambivalence/hesitancy recognition in unconstrained videos is a challenging problem due to the subtle, multimodal, and context-dependent nature of this behavioral state. In this paper, a multimodal approach for video-level ambivalence/hesitancy recognition is presented for the 10th ABAW Competition. The proposed approach integrates four complementary modalities: scene, face, audio, and text. Scene dynamics are captured with ...

Added: September 30, 2026

Профессиональная учебная практика: I курс. Введение в биотехнологию, клеточную и молекулярную биологию : учебно-методическое пособие для студентов и преподавателей

Knyazev E., Чеботарева О. Е., М.: Издательский дом НИУ ВШЭ, 2026.

This teaching and learning guide provides a concise overview of the theoretical and practical aspects of the basic skills required to work in a biological laboratory. It also includes protocols for practical classes conducted as part of the introductory professional training placement for first-year students in the Bachelor’s programme in Cell and Molecular Biotechnology at ...

Added: September 30, 2026

Decoding Algorithms for Binary U-UV Codes: A Unified Survey of Performance and Complexity

Ivanov F., Kotov F., IEEE Access 2026 Vol. 14 P. 104662–104679

U-UV codes, based on the Plotkin (U, U + V) construction, provide a unified framework that includes polar and Reed–Muller codes and enables flexible design through the choice of component codes. While modern capacity-approaching codes achieve excellent performance at large block lengths, their efficiency at short and moderate lengths remains limited, especially under low-latency constraints. ...

Added: September 30, 2026

The EG-TD3 Machine Learning Architecture: Evolutionary-Guided Twin Delayed Deep Deterministic Policy Gradient

Djambong Tenkeu H., Institute for System Programming of the RAS, 2026.

Added: September 29, 2026

Анализ in silico вероятных зависимостей «структура-активность» этанола

Ryskina H., Knyazev E., Вопросы биологической, медицинской и фармацевтической химии 2026 Т. 29 № 9 С. 84–91

Introduction. The active integration of rapidly developing omics and computer technologies in the 21st century has led to a breakthrough in understanding the principles of the functioning of living systems. One of the dynamically developing integrative areas in biology is biological modeling. The fundamental paradigm has been the methodology that allows for the prediction of ...

Added: September 29, 2026

Нижние множества и свойства замкнутости классов функций подсчета

Ivanashev Y., Доклады Российской академии наук. Математика, информатика, процессы управления (ранее - Доклады Академии Наук. Математика) 2026 Т. 529 С. 93–101

Язык L является нижним для релятивизируемого сложностного класса C, если CL=C. Для классов #P, GapP и SpanP известны точные нижние классы языков: Low(#P) = UP ∩ coUP, Low(GapP) = SPP и Low(SpanP) = NP ∩ coNP. В этой статье мы доказываем, что Low(TotP) = P, и приводим характеризации нижних классов функций для #P, GapP, TotP ...

Added: September 28, 2026

Role of dislocations in the mobility of pinned helium bubbles: Molecular dynamics simulations in aluminum

Piliugin L., Antropov A., Lobashev E. et al., Journal of Nuclear Materials 2026 Vol. 632 Article 156876

The effects of dislocations on the mobility of gas nanobubbles pinned to them are considered as novel unex- plored mechanisms of accelerated fission gas release and investigated using classical molecular dynamics of helium bubbles in FCC aluminum. Non-equilibrium methods are developed to calculate the mobility of a pinned bubble both along and across the dislocation ...

Added: September 28, 2026

MPI+OpenMP implementation of resolution-of-the-identity Hartree-Fock method exploiting permutational symmetry of three-center electron repulsion integrals

Kashpurovich I., Oleynichenko A., Stegailov V., Supercomputing Frontiers and Innovations 2026 Vol. 13 No. 1 P. 52–73

We report a high-performance implementation of the resolution-of-the-identity Hartree–Fock method that fully exploits the permutational symmetry of three-center electron repulsion integrals (ERI). The present implementation adopts a hybrid MPI+OpenMP parallelization strategy. Two different algorithmic approaches (with and without the pre-transformation of ERIs) are compared. A custom data layout introduced previously is employed. Designed to efficiently ...

Added: September 28, 2026

A Three-Party W-State Quantum Secret Sharing Protocol with X-Gate Encoding and Forbidden-Outcome Detection

Teregulov T., Loubenets E. R., / Series Quantum Physics "arXiv". 2026. No. 2609.31472.

We develop a new three-party quantum secret-sharing (QSS) protocol based on a three-qubit W state. This protocol encodes the secret-sequence bits using X gates and employs randomly selected Hadamard operations and measurement bases to generate information and security-test rounds. We evaluate the efficiency of the proposed protocol and analyze its security against an internal adversary ...

Added: September 28, 2026

Kolmogorov–Arnold networks for genomic tasks

Cherednichenko O., Poptsova M., Briefings in Bioinformatics 2025 Vol. 26 No. 2 Article bbaf129

Kolmogorov–Arnold networks (KANs) emerged as a promising alternative for multilayer perceptrons (MLPs) in dense fully connected networks. Multiple attempts have been made to integrate KANs into various deep learning architectures in the domains of computer vision and natural language processing. Integrating KANs into deep learning models for genomic tasks has not been explored. Here, we ...

Added: June 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 ...

Added: May 19, 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

Utilizing the VirIdAl Pipeline to Search for Viruses in the Metagenomic Data of Bat Samples

Budkina A., Korneenko E., Kotov I. et al., Viruses 2021 No. 10 P. 2006

According to various estimates, only a small percentage of existing viruses have been discovered, naturally much less being represented in the genomic databases. High-throughput sequencing technologies develop rapidly, empowering large-scale screening of various biological samples for the presence of pathogen-associated nucleotide sequences, but many organisms are yet to be attributed specific loci for identification. This ...

Added: September 19, 2025