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July 20, 2026
Scientists Create Open Dataset for Studying Concentration
A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.
July 20, 2026
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Fuad Aleskerov, Tenured Professor and Director of the International Centre of Decision Choice and Analysis at HSE University, together with his colleagues, has developed methods of network analysis in bibliometrics that have made it possible to identify patterns in the appearance and citation of publications in academic journals, as well as their influence on each other. When one or a number of studies are frequently cited by a wide range of journals, this is an indicator that the research is of high quality. By contrast, extensive cross-citation within a limited group of journals increases the likelihood of identifying a network of predatory publications.
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An international group of researchers, including mathematicians from the AI and Digital Science Institute at the HSE Faculty of Computer Science, has provided a theoretical justification for a simple and computationally efficient method of estimating uncertainty in Stochastic Gradient Descent (SGD). The paper has been published on the scientific preprint server arXiv.org and presented at AISTATS 2026.

 

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Association of Z-RNA with QTL variants

.
Glimanova D.

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 phenotype. Here we performed analysis of Z-DNABERT predicted Z-flipons that have variants reported in GWAS studies and overlap with expression and splicing QTL in different tissues. We analyzed around 70 DNA variants mapped to the predicted Z-flipons and found that half of them do not affect Z-RNA formation and presumably has an effect at the DNA level. For the remaining the effect was seen at the level of RNA formation. We discovered variants associated with various diseases: pulse pressure, atrial fibrillation and atrial flutter (rs74181299(T>C)), height, thumb osteoarthritis and hip circumference adjusted for BMI (rs11588850(A>G)), sleep duration (short sleep) (rs205024(C>T)), low density lipoprotein cholesterol levels and total cholesterol levels (rs72658867(G>A)), Youthful appearance, schizophrenia (rs138880(A>C)). All the reported variants affect Z-RNA formation by disrupting RNA stems regardless of short or long RNA sequence length is considered. They are often located in the introns and influence expression of other genes in the regions. Some of the reported variants also affect splicing of the same gene they are in or nearby genes. Additionally, we performed haplotype analysis and showed that other variants that are included in the haplotype do not overlap with any known functional genomic elements. Overall, our analysis highlights the potential association of Z-flipons with diseases.

Language: English
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Keywords: non-B DNAZ-DNAZ-ДНК

In book

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