HSE Scientists Develop DeepGQ: AI-based 'Google Maps' for G-Quadruplexes
Researchers at the HSE AI Research Centre have developed an AI model that opens up new possibilities for the diagnosis and treatment of serious diseases, including brain cancer and neurodegenerative disorders. Using artificial intelligence, the team studied G-quadruplexes—structures that play a crucial role in cellular function and in the development of organs and tissues. The findings have been published in Scientific Reports.
DNA can be thought of as a long chain of symbols made up of four letters: A, C, G, and T. Beyond the sequence itself, the way the DNA strand is folded and twisted is also crucial. This structure determines which regions of the genetic code are open—accessible to the cell for reading and replication—and which remain closed. One form of such 'packaging' is a special structure known as a G-quadruplex. It can be visualised as a small nodular structure that forms in regions rich in guanine (G). Scientists have hypothesised that each cell type has its own unique set of such nodules, which helps determine the cell’s function. For example, the DNA of nerve cells in the brain differs from that of liver cells in the pattern of these specialised structures. These variations influence how different cell types develop and function. However, investigating these processes in the laboratory is expensive and does not always produce reliable results.
Researchers at the HSE AI Research Centre have developed the DeepGQ AI model, which uses deep learning to generate tissue-specific maps of G-quadruplexes. The model analyses the DNA strand in both directions simultaneously, much like reading it from left to right and from right to left. This bidirectional approach allows the program to capture a complete and accurate picture of the features of the DNA region under study.
Artem Bashkatov, Junior Research Fellow at the Centre for Biomedical Research and Technology of the AI and Digital Science Institute, explains: 'We hypothesised that the characteristics of the cellular environment—not only the DNA structure itself—play a key role in determining how different tissue-specific cell types develop. To test this idea, we developed not a single universal model, but a set of specialised DeepGQ models tailored to different tissues. For example, one model was trained exclusively on brain cells (DeepGQ Neurons), another on liver cells (DeepGQ Liver), and so on across 14 tissue types. This approach enabled each model to identify developmental patterns specific to its tissue.'
Thanks to DeepGQ, scientists now have access to a tool that enables highly accurate prediction of G-quadruplexes. Rather than relying on costly experimental studies, any laboratory investigating, for example, liver cancer or Alzheimer’s disease can use data from patient samples and apply DeepGQ to generate an accurate map of the most likely targets for experimental validation.
'DeepGQ is essentially like Google Maps for G-quadruplexes: it plots landmarks (GQs) and traffic conditions (DHSs and histones) onto a flat DNA map that is unique to each "city," or tissue,' says Maria Poptsova, Director of the Centre for Biomedical Research and Technology at the Institute of AI and Digital Sciences. 'Many serious diseases—from cancer to neurodegeneration—are disorders of lost tissue identity. Cells either forget what they are meant to become, or their specialisation programmes break down. G-quadruplexes may become promising new targets for the treatment of such diseases. If a cancer cell depends on a specific GQ structure for its survival, it may be possible to develop a drug that either disrupts or stabilises this structure until the cellular programme collapses, ultimately killing the cancer cell. In the future, this approach could lead to the creation of a DeepGQ Patient model: by analysing data from a tumour biopsy, researchers could generate a personalised map of active G-quadruplexes and use it to design a truly individualised treatment strategy.'
See also:
Resource Race and Green Transition: Three Unexpected Conclusions from Foresight Centre’s Research on Climate and Poverty
Beneath the surface of green energy—which most people associate with solar panels, electric vehicles, and reduced CO2 emissions—lies a complex web of geopolitical interests, international inequality, and resource constraints. Researchers from the Laboratory for Science and Technology Studies (LST) at the HSE ISSEK Foresight Centre have published a series of articles in leading international journals on hidden and overt conflicts surrounding critically important metals and minerals, as well as related processes in the energy sector.
Immersion in Second Language Environment Influences Bilinguals’ Perception of Emotions
Researchers at the Cognitive Health and Intelligence Centre at the HSE Institute for Cognitive Neuroscience have discovered how bilingual individuals process emotional words in their native (first) and non-native (second) languages. It was found that the link between word meaning and bodily sensations is weaker in a second language than in a first language. However, the more a person is immersed in a language environment, the smaller this difference becomes. The article has been published in Language, Cognition and Neuroscience.
HSE Students Among Winners of Yandex High-Tech Startup Accelerator
Yandex has announced the results of its Yandex AI Startup Lab accelerator, whose final round featured 12 IT projects. Over the course of three months, their creators—students and young entrepreneurs—worked alongside the company’s experts to develop their products. Four startups in digital marketing, medicine, and robotics were named the best, with their teams receiving cash prizes and cloud resource grants. Among them was Gradius, a startup founded by students from HSE University.
Researchers Find More Effective Approach to Revealing Majorana Zero Modes in Superconductors
An international team of researchers, including physicists from HSE MIEM, has demonstrated that nonmagnetic impurities can help more accurately reveal Majorana zero modes—quantum states considered promising building blocks for quantum computing. The researchers found that these impurities shift the energy levels that typically obscure the Majorana signal, while leaving the mode itself largely unaffected, thereby making its spectral peak more distinct. The study has been published in Research.
New Development by HSE Scientists Helps Design Reliable Electronics Faster at a Lower Cost
Scientists from HSE MIEM have developed a new approach to modelling electrothermal processes in high-power electronic circuits on printed circuit boards (PCB). The method allows engineers to quickly and accurately predict how electronic components heat up during operation, helping prevent overheating and potential failures. The results have been published in Russian Microelectronics.
The Future of Cardiogenetics Lies in Artificial Intelligence
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a program capable of analysing regions of the human genome that were previously inaccessible for accurate interpretation in genetic testing. The program adapts large generative AI (GenAI) models for cardiogenetics to predict how specific mutations affect the function of individual genes.
HSE Researchers: Young Russians Have Sufficient Knowledge About Money but Lack Money Management Skills
Adolescents and young adults in Russia today are well versed in financial terminology: they know what bank cards, loans, interest rates, and online payments are. However, as researchers at HSE University have found, real money-management skills remain poorly developed among most young people. The study ‘Financial Literacy, Financial Culture, and Financial Autonomy of Youth’ has been published in Monitoring of Public Opinion: Economic and Social Changes.
Why Weaker Competitors Give Up—and How to Keep Them in the Game
Anastasia Antsygina, Assistant Professor at HSE University’s Faculty of Economic Sciences, has developed a prize distribution model that maximises competitor engagement. She proposed revising the traditional ‘winner-takes-all’ approach and, in certain cases, offering a small reward even to those who have lost. According to her, this could increase participant motivation and make the competition more intense. The findings of her research were published in the Economic Theory journal.
HSE Researchers Compile Scientific Database for Studying Children’s Eating Habits
The database created at HSE University can serve as a foundation for studying children’s eating habits. This is outlined in the study ‘The Influence of Age, Gender, and Social-Role Factors on Children’s Compliance with Age-Based Nutritional Norms: An Experimental Study Using the Dish-I-Wish Web Application.’ The work has been carried out as part of the HSE Basic Research Programme and was presented at the XXVI April International Academic Conference named after Evgeny Yasin.
New Foresight Centre Study Identifies the Most Destructive Global Trends for Humankind
A team of researchers from the HSE International Research and Educational Foresight Centre has examined how global trends affect the quality of human life—from life expectancy to professional fulfilment. The findings of the study titled ‘Human Capital Transformation under the Influence of Global Trends’ were published in Foresight.