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  • Алгоритм для вычисления полных вероятностей сборки Т-клеточных рецепторов альфа-бета цепей
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News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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?

Алгоритм для вычисления полных вероятностей сборки Т-клеточных рецепторов альфа-бета цепей

С. 96–96.
Назаров В.И., Погорелый М. В., Звягин И. В., Лебедев Ю. Б., Мамедов И. З.
Language: Russian
Keywords: bioinformaticsбиоинформатика

In book

XXVII Зимняя молодежная научная школа "Перспективные направления физико-химической биологии и биотехнологии"
М.: ИБХ РАН, 2015.
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Optimizing Computational Infrastructure for Large Language Models in Bioinformatics: A Case Study
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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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Multimodal graph, surface, and language-based model for protein protein interaction prediction
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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 ...
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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 ...
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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 ...
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Transcriptomic Maps of Colorectal Liver Metastasis: Machine Learning of Gene Activation Patterns and Epigenetic Trajectories in Support of Precision Medicine
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Новая эра биоинформатики
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Биоинформатика — это быстро развивающаяся дисциплина на стыке биологии, информатики и математики. Научно-технический прогресс в области биологических и биомедицинских наук за последние годы привел к стремительному росту объемов данных. Для анализа и интерпретации больших данных нужны мощные вычислительные инструменты и специалисты с глубокими знаниями в различных областях, включая молекулярную биологию, генетику, программирование и математику. В ...
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Genome-wide association studies of ischemic stroke based on interpretable machine learning
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Despite the identification of several dozen genetic loci associated with ischemic stroke (IS), the genetic bases of this disease remain largely unexplored. In this research we present the results of genome-wide association studies (GWAS) based on classical statistical testing and machine learning algorithms (logistic regression, gradient boosting on decision trees, and tabular deep learning model ...
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Proceedings of Science, volume 429. The 6th International Workshop on Deep Learning in Computational Physics
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The Workshop will be held in the Meshcheryakov Laboratory of Information Technologies (MLIT) of the Joint Institute for Nuclear Research (JINR) on July 6-8, 2022. The workshop primarily focuses on the use of machine learning in particle astrophysics and high energy physics, but is not limited to this area. Topics of interest are various applications of ...
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Unsupervised domain adaptation methods for cross-species transfer of regulatory code signals
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Proceedings of 11th Moscow Conference on Computational Molecular Biology MCCMB'23
IITP RAS, 2023.
В сборнике представлены тезисы работ участников 11-ой Московской конференции по вычислительной молекулярной биологии MCCMB'23. Работы посвящены актуальным вопросам анализа аминокислотных и нуклеотидных последовательностей, структур биополимеров, молекулярной эволюции, методов высокопроизводительного секвенирования, системной биологии и биоалгоритмов. ...
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10th International Conference, PReMI 2023, Kolkata, India, December 12–15, 2023, Proceedings. Pattern Recognition and Machine Intelligence. LNCS, volume 14301
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Cross-Domain Limitations of Neural Models on Biomedical Relation Classification
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Proceedings of the 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics
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GFAP-IL6 transgenic mice are characterised by astroglial and microglial activation predominantly in the cerebellum, hallmarks of many neuroinflammatory conditions. However, information available regarding the proteome profile associated with IL-6 overexpression in the mouse brain is limited. This study investigated the cerebellum proteome using a top-down proteomics approach using 2-dimensional gel electrophoresis followed by liquid chromatography-coupled ...
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Characterisation of the Mouse Cerebellar Proteome in the GFAP-IL6 Model of Chronic Neuroinflammation
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GFAP-IL6 transgenic mice are characterised by astroglial and microglial activation predominantly in the cerebellum, hallmarks of many neuroinflammatory conditions. However, information available regarding the proteome profile associated with IL-6 overexpression in the mouse brain is limited. This study investigated the cerebellum proteome using a top-down proteomics approach using 2-dimensional gel electrophoresis followed by liquid chromatography-coupled ...
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MATHEMATICAL MODELING AND HIGH-PERFORMANCE COMPUTING IN BIOINFORMATICS, BIOMEDICINE AND BIOTECHNOLOGY (MM-HPC-BBB-2018). The 3rd International Symposium
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Proceedings of the 26th Conference of Open Innovations Assosiation FRUCT
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Magnesium chelatase chlIDH and cobalt chelatase cobNST enzymes are required for biosynthesis of (bacterio)chlorophyll and cobalamin (vitamin B12), respectively. Each enzyme consists of large, medium, and small subunits. Structural and primary sequence similarities indicate common evolutionary origin of the corresponding subunits. It has been reported earlier that some of vitamin B12 synthesizing organisms utilized unusual ...
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Proceedings of 10th Moscow Conference on Computational Molecular Biology MCCMB'21
M.: IITP RAS, 2021.
10th Moscow Conference on Computational Molecular Biology MCCMB'21 ISBN 978-5-901158-32-6 ...
Added: September 10, 2021
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