?
CSDB/SNFG Structure Editor: an online glycan builder with 2D and 3D structure visualization
Journal of Chemical Information and Modeling. 2021. Vol. 61. No. 10. P. 4940–4948.
Bochkov A., Toukach Ph.
This article describes features, usage, and application of an CSDB/SNFG Structure Editor, a new online tool for quick and intuitive input of carbohydrate and derivative structures using Symbol Nomenclature for Glycans (SNFG). The Editor is built on a platform of the Carbohydrate Structure Database (CSDB) and relies on its online services via the dedicated web-API. The Editor allows building of oligo- and polymeric glycan structures and supports most features of natural glycans, such as underdetermined structures, alternative branches, repeating subunits, SMILES specification of atypical monomers, and others. The vocabulary of building blocks contains 600+ monomeric residues, including 327 monosaccharides. Support for SMILES allows input and visualization of chemical structures of virtually unlimited complexity. On the other hand, the interface follows the recognized GlycanBuilder style easy to novice users. The export feature includes support for CSDB Linear, GlycoCT, WURCS, SweetDB, and Glycam notations, SMILES codes, MOL/PDB atomic coordinate formats, raster and vector SNFG images, and on-the-fly visualization as 2D structural formulas and 3D molecular models. Integration of the Editor into any web-based glycoinformatics project is straightforward and simple, similarly to any other modern JavaScript application.
Snegirev A., Sychev S., Futures 2026 Vol. 183 P. 1–22
This study addresses the systemic identification and categorization of risks associated with AI development, arising from tensions between technological evolution and institutional, infrastructural, and economic contexts. Drawing on a constructionist methodology, we interpret technological risks as constitutive elements of expert communities' images of the future. Through in-depth interviews with 100 AI experts, proportionally representing corporate, ...
Added: September 23, 2026
Parshakov P., Paklina S., International Journal of Human-Computer Interaction 2026 P. 1–17
This study examines how emotional tone shapes user preference in human–large language model (LLM) interaction. Drawing on the Computers as Social Actors framework, we treat conversational AI as a social communicator whose affective cues influence user judgments. Using large-scale pairwise preference data from LMSYS Chatbot Arena, we model emotional tone through the Valence–Arousal–Dominance framework and ...
Added: September 23, 2026
Andrabi U., Wadood E., Ojha S. K. et al., IEEE Access 2026 Vol. 14 P. 103358–103375
The emergence of 5G networks, aimed at accommodating diverse service requirements such as enhanced Mobile Broadband (eMBB), Ultra-Reliable Low-Latency Communication (URLLC), and massive Machine-Type Communication (mMTC), has presented significant challenges in radio resource management and network slicing. In dynamic heterogeneous network systems, traditional heuristics and mathematical programming methods find it challenging to attain scalable multi-objective ...
Added: September 23, 2026
Paklina S., Parshakov P., Elena Rapoport, Scientometrics 2026 P. 1–26
Generative artificial intelligence has become a routine part of academic writing. While much of the debate has focused on questions of integrity and authorship, less attention has been paid to how AI-assisted writing may affect research evaluation itself. This paper asks a straightforward but important question: does the use of LLMs in academic writing change ...
Added: September 23, 2026
Diachkova E., Nikulin D., Кубкин Я. В. et al., American Journal of Respiratory and Critical Care Medicine 2026 Vol. 212
Accurate classification of a patient with pulmonary hypertension (PH) into one of five groups is fundamental for appropriate disease management strategies. The time from disease onset to correct diagnosis is unacceptably long in many cases. Chronic thromboembolic pulmonary hypertension (CTEPH) develops as a consequence of venous thromboemboli, resulting in a more pronounced hereditary predisposition to ...
Added: September 23, 2026
Xu Y., Ryabov F., Alexandrov I. et al., USA 2026 Vol. 6 No. 8 Article 101324
Центромеры обеспечивают расхождение хромосом, однако организацию их хроматина в пределах повторяющейся альфа-сателлитной ДНК долгое время было трудно изучать. Для решения этой задачи мы создали гаплотип-разрешённые аннотации сателлитной ДНК для полной диплоидной сборки генома человека T2T-HG002. Затем с помощью метода направленного метилирования с секвенированием длинных прочтений (DiMeLo-seq) мы картировали центромерный белок A (CENP-A), модификацию H3K9me3 и ...
Added: September 23, 2026
Hebbar P., Ryabov F., Alexandrov I. et al., Cell 2026 Vol. 189 P. 4891–4908.e12
The common marmoset is a New World monkey widely used to study primate evolution and human disease. We present a telomere-to-telomere (T2T) reference assembly for the species, plus three near-T2T haplotypes. These resolve previously inaccessible regions, including the centromeres, sex chromosomes, subterminal satellites, acrocentric chromosomes, and the major histocompatibility complex (MHC). We find marmoset centromeres ...
Added: September 23, 2026
Kertesz-Farkas A., Acquaye F. L., Journal of Proteome Research 2026 Vol. 25 P. 3764–3768
Ultimately, most tandem mass spectrometry (MS/MS) proteomics experiments aim to not just detect but also quantify the proteins in a given complex sample. Here, we describe an extension to the Crux MS/MS analysis toolkit to enable label-free quantification of peptides. We demonstrate that Crux’s new quantification command, which is modeled after the algorithms implemented in ...
Added: September 23, 2026
Budkov Y., Journal of Chemical Physics 2026 Vol. 165 No. 12 Article 124105
Exact theories of electrolyte structure must satisfy the nonlocal constraints imposed by electrostatic screening, yet these constraints are most commonly formulated only for homogeneous bulk systems and at the level of two-point correlations. Here, we develop a unified field-theoretic framework that extends them to general inhomogeneous ionic fluids and nonlinear charge correlations. Using a standard ...
Added: September 22, 2026
Maddalena L., Yildiz B., Del Vecchio Blanco F. et al., Risk Analysis 2026 Vol. 46 No. 4 P. 1–26
Heated tobacco products (HTPs) are marketed as alternatives to conventional cigarettes with a potential reduced risk profile. Yet, their actual impact on cancer and noncancer disease risk remains uncertain and requires rigorous quantitative assessment. In this study, we develop a unified and transparent computational framework for toxicological risk assessment of HTPs, integrating chemical emissions data ...
Added: September 22, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Pattern Recognition and Image Analysis 2024 Vol. 34 No. 3 P. 855–862
Tasks related to the automation of medical data processing are becoming more urgent. Particular attention is paid to systems for monitoring and analyzing human physiological parameters. Such systems often use specialized sensors to capture biomedical images, such as infrared cameras. This article describes our study of the problem of segmenting the eye pupil and iris ...
Added: September 21, 2026
Aleksei Samarin, Nazarenko A., Alexander Savelev et al., Pattern Recognition and Image Analysis 2024 Vol. 34 No. 3 P. 844–854
Improving image quality is becoming an increasingly popular task, especially when working with mobile devices. One common approach to image enhancement is the use of convolutional neural networks. However, to achieve good results, such networks must be large enough, otherwise there is a risk of unwanted artifacts. In addition, large convolutional neural networks require significant ...
Added: September 21, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Optical Memory and Neural Networks (Information Optics) 2024 Vol. 33 P. 424–434
This study explores the development of classifiers for microbial images, specifically focusing on streptococci captured via microscopy of live samples. Our approach uses AutoML-based techniques and automates the creation and analysis of feature spaces to produce optimal descriptors for classifying these microscopic images. This technique leverages interpretable taxonomic features based on the external geometric attributes ...
Added: September 21, 2026
Aleksei Samarin, Aleksei Toropov, Alexander Savelev et al., Pattern Recognition and Image Analysis 2024 Vol. 34 No. 4 P. 1053–1060
This paper presents a novel approach to classification in biomedical imaging, specifically targeting polyp recognition in video endoscopy snapshots. Our method leverages specialized image descriptors to enhance the accuracy and robustness of polyp recognition. By employing these specialized descriptors, we address the challenges inherent in analyzing biomedical images from open datasets. Our approach not only ...
Added: September 21, 2026
Самарин А. В., Торопов А. Г., Савельев А. Г. et al., Pattern Recognition and Image Analysis 2024 Vol. 34 No. 4 P. 1044–1052
This paper presents a study aimed at improving the detection quality of small-sized microorganisms under challenging microscopic conditions through the application of a lightweight combined image preprocessing model. We focused on the task of detecting diplococci in images obtained through dynamic sample microscopy. The proposed approach employs predefined filters for image preprocessing, combined with the ...
Added: September 21, 2026
Singapore: Springer Singapore, 2025.
Added: September 21, 2026
Tomat A., Sergei O. Kuznetsov, International Journal of Approximate Reasoning 2026 Vol. 197 Article 109754
Interval Pattern Structures (IPS) provide a natural way to represent local, human-readable explanations for predictions on numerical data through vectors of intervals interpreted as axis-parallel hyper-rectangles. In this paper, we develop and evaluate an IPS-based k-nearest neighbors classifier, IPS-KNN, that explains each prediction through a single local interval description rather than through the aggregation of ...
Added: September 21, 2026
Aleksei Samarin, Nazarenko A., Kotenko E. et al., / Series arXiv "math". 2025. No. 2511.20141.
This paper presents a novel approach to neural network compression that addresses redundancy at both the filter and architectural levels through a unified framework grounded in information flow analysis. Building on the concept of tensor flow divergence, which quantifies how information is transformed across network layers, we develop a two-stage optimization process. The first stage ...
Added: September 21, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Pattern Recognition and Image Analysis 2025 Vol. 35 No. 2 P. 169–178
This study explores the incorporation of specialized self-attention mechanisms into deep learning architectures, with a particular emphasis on segmenting human iris and pupil regions in infrared images. In this work, we present some modified versions of nonlocal blocks designed to enhance self-attentive properties while addressing the distinct characteristics of infrared imaging data. By applying these customized ...
Added: September 21, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Journal of Imaging 2025 Vol. 11 No. 10 Article 359
Timely identification and accurate delineation of ultra-early ischemic stroke lesions in non-contrast computed tomography (CT) scans of the human brain are of paramount importance for prompt medical intervention and improved patient outcomes. In this study, we propose a deep learning-driven methodology specifically designed for segmenting ultra-early ischemic regions, with a particular emphasis on both the ...
Added: September 21, 2026
Agafoshin M., Gorokhov S., Dmitriev R., Geography and Natural Resources 2024 Vol. 45 No. 4 P. 436–443
This study focuses on the role of a specific unit in the spatial structure of the migration system: the
transit region. As a consequence of a sharp increase in the number of asylum seekers and refugees, there has
been a rise in the duration of their stay in temporary accommodation centers (TACs)—the main form of their
resettlement in ...
Added: February 14, 2025
Toukach P., Analytical and Bioanalytical Chemistry 2025 Vol. 417 P. 1025–1034
Carbohydrate Structure Database (CSDB) is a curated glycan data collection and a glycoinformatic platform. In this report, its database, analytical, and other components that have appeared for the recent years, are reviewed. The major improvements were achieving close-to-full coverage on glycans from microorganisms, launching modules for glycosyltransferases and saccharide conformations, online glycan builder and 3D ...
Added: October 9, 2024
Toukach P., Glycobiology 2023 Vol. 33 No. 7 P. 528–531
Carbohydrates structures in the Carbohydrate Structure Database have been referenced to glycoepitopes from the Immune Epitope Database allowing users to explore the glycan structures in the context of epitopes they contain. Starting with an epitope, one can figure out the glycans from other organisms that share the same structural fragment, and retrieve the associated taxonomical, ...
Added: October 9, 2024
R. V. Dmitriev, Gorokhov S. A., Agafoshin M. M., R-Economy 2023 Vol. 9 No. 2 P. 140–154
Relevance. The development of central place theory has been hindered by its static nature, as it fails to capture transitions between equilibrium states in central place systems. This long-standing problem remains unsolved since the theory's inception 90 years ago. This article presents a solution by examining the cases of system unification and system breakup, where ...
Added: February 16, 2024