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Regular version of the site

Seminars 2022/2023

12.01.2022 [online] Non-canonical transcripts of HSV-1

Zoom

Speaker: Fedorov Alexander, junior researcher

The eighty known open reading frames (ORFs) of HSV-1 have been extensively studied over decades. However, the actual number of RNA transcribed from the viral genome is much higher and amounts to several hundred. Some of them encode previously undescribed but experimentally confirmed proteins. Others are probably just 5' elongated isoforms. These and many other facts about the biological role of non-canonical HSV-1 transcripts will be discussed in detail during the report.

09.02.2022 [online] Role of ICP27 in cells infected with HSV-1

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Speaker: Fedorov Alexander, junior researcher

Virus infections, including HSV-1, cause massive disruption of transcription termination (DOTT) in host cells. However, the underlying mechanisms of this process remain a mystery. It has been experimentally shown that ICP27, one of 80 HSV-1 proteins, is able to induce DOTT by direct binding to the 3' end processing factors of some host RNAs. At the same time, ICP27 plays an important role in the correct termination of viral RNA transcription. These and other facts will be described in detail during the report.

16.03.2022 [online] Interaction between tumor cells and its microenvironment: detection of ligand-receptor pairs

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Speaker: Osintseva Ekaterina, Master's student of «Data Analysis in Biology and Medicine» program

The study of the heterogeneity of the tumor microenvironment and the interaction of its cells with each other and with the tumor may help to reveal the mechanisms by which the tumor avoids the immune response. Understanding these mechanisms is of value in the first place for the development of various methods of immunotherapy.

Using the CellChat package for 8 scRNA-seq samples of metastases in the brain parenchyma, pairs of interactions between different cell types were found according to the ligand-receptor principle. Primary analysis showed in all samples the presence of interactions between cells through the MIF ligand, in particular, this interaction was observed between metastatic cells and cells of the immune system. Literature review has shown that such interactions can lead to tumor progression and immunosuppression.

16.04.2022 [online] Analysis of cell death pathways in populations of tumor cells and its microenvironment

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Speaker: Osintseva Ekaterina, Master's student of «Data Analysis in Biology and Medicine» program

Today, the term "tumor microenvironment" refers to the totality of components of a solid tumor, including its vasculature, tumor-associated fibroblasts, various immune cells, and extracellular matrix. The study of cell death pathways in the context of malignant neoplasms is important for two reasons: firstly, the activation of cell death programs in tumor cells can be used as a cancer therapy technique, and secondly, the "fratricide" of various immune cell populations can affect the progression of the disease and the avoidance of the immune response by the tumor.

This report will highlight the results of the analysis of the activity of cell death pathways in 8 scRNA-seq samples of metastases in the brain parenchyma.

25.05.2022 [online] The role of flipons and miRNAs in determining promoters at early stages of development

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Speaker: Pavlov Fedor, PhD student

There are several points of view on the mechanisms by which gene regulation is carried out. The results of computational experiments suggest that in these processes there is a deep connection between the mechanisms of RNA and DNA. The report presents data supporting a model in which flipons open binding sites for miRNAs, leading to the creation of bivalent promoters early in development. The results of computational experiments are presented, which indicate a clear predominance of certain groups of flipons as the most preferred candidates for binding to regions of conserved miRNAs.

22.06.2022 [online] Prediction of Z-DNA regions in the human and mouse genomes

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Speaker: Beknazarov Nazar, junior researcher

The role of Z-DNA in cellular processes is known, and over time, an increasing involvement of this DNA structure in the regulation of expression, the immune response, and many other processes has been discovered. Therefore, the study and prediction of Z-DNA regions in various organisms has become of current interest. The report presents experiments on the prediction of Z-DNA by machine learning models trained on experimental labeling and analysis of the predictions obtained, followed by a comparison of the findings obtained on different organisms.

13.07.2022 [online] RNA editing landscape in Alzheimer's disease

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Speaker: Konovalov Dmitry, trainee researcher

Alzheimer's disease is one of the most common neurodegenerative diseases. Research into disease-specific RNA editing may shed light on new methods to combat it. The report will describe the currently available data on RNA editing, the ADeditome database, and the possible role of flipons in the regulation of neurodegenerative processes.

24.08.2022 [online] Comparison of the quality of various methods of domain adaptation in bioinformatics problems

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Speaker: Latyshev Pavel, PhD student

A report was presented on a comparative study of 9 methods of domain adaptation: ADDA, AFN, CDAN, DAN, DANN, JAN, MCC, MCD, MDD. These methods have been applied to various histone marks and transcription factors on the human, mouse, nematode, drosophila, and yeast genomes. Comparative tables with quality metrics on various tasks were shown and analyzed.

21.09.2022 [online] LGP2 and its role in the regulation of IFN-response in cells with inactivated ADAR1

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Speaker: Fedorov Alexander, junior researcher

RNA editing by adenosine deaminase ADAR1 prevents the cellular immune response to endogenous RNAs. In cells with inactivated ADAR1, unedited self-RNAs form base-pair structures that resemble viral RNAs and inadvertently activate the MDA5 receptor, leading to a type I IFN-response. However, MDA5 is not the only receptor required to induce an immune response. Another essential receptor is LGP2.

12.10.2022 [online] Transcription factor Aire

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Speaker: Pavlov Fedor, PhD student

Aire (autoimmune regulator) is a protein that plays a significant role in the regulatory processes of the genome due to its active involvement in the formation of tolerance of the immune system. To date, it is known that Aire is responsible for the regulation of thousands of genes, but there is no understanding of the specific mechanisms through which this regulation is carried out. The report discusses the interaction analysis of Aire and four sets of Z-DNA regions that were obtained using computational and experimental methods. The results of bulk RNA-seq analysis of Aire-KO data are presented, as a result of which a target group of Aire-activated genes in the mouse organism is isolated.

26.10.2022 [online] Cis-regulatory elements and Z-flipons

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Speaker: Konovalov Dmitry, trainee researcher

Cis-regulatory elements are regions of nucleic acids that regulate the expression of genes located on the same molecule. Flipons located in these regions can regulate gene expression by changing the secondary structure of DNA. This report will present the results of the analysis of the localization of Z-flipons and describe the main methods of conducting: determining the coordinates of cis-regulatory elements, studying the association of traits, and determining the genes and processes potentially regulated by this mechanism.

16.11.2022 [online] Investigation of the DANN domain adaptation method for predicting G-quadruplexes

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Speaker: Latyshev Pavel, PhD student

The report presented the use of domain adaptation for machine learning models trained on one organism for reuse on other organisms. The quality of adaptation was studied on the G4-ChIP-Seq and G4-Seq datasets on human and mouse DNA.

16.01.2023 [online] Graph Neural Networks for Predicting DNA Secondary Structures

Speaker: Artyom Voytetsky, trainee researcher

The report presented three modules that carry out training, testing various graph networks based on the prepared data, and also draws additional graphs (ROC-, PR- and F1 score curves).

20.02.2023 [online] Z-DNA segment prediction pipeline

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Speaker: Anna Danilova, trainee researcher

The report has been updated by a program that is a pipeline for learning and runs a Transformer that predicts Z-DNA regions.

13.03.2023 [online] Inverted repeats in the eukaryotic genome: structure and functions

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Speaker: Aleksandr Fedorov, Junior Researcher

A significant, and often overwhelming, portion of eukaryotic genomes is composed of repetitive sequences. DNA repeats are extremely diverse in nature and often do not have a defined biological function. However, among the variety of eukaryotic repeats, inverted repeats (IRs) stand out separately. Based on a series of experiments, we know that some of them tend to form cruciform structures in DNA, which are involved in replication, transcriptional regulation, and chromatin organization. Additionally, during transcription, IR can form long segments of double-stranded RNA, which are critical for innate immune response and can further be processed into small interfering RNAs with various functions. These and other details of IR biology will be discussed during the presentation.

17.04.2023 [online] A non-cooperative framework for cooperative action: a generalized Nash program

Pokrovsky Boulevard 10, Auditorium R406

Speakers:  Dmitry Levando, Candidate of Economic Sciences

We demonstrate how to build coalition structures with any number of coalitions from non-coalitional actions of individual agents. The approach extends the traditional non-cooperative Nash game to the area of non-cooperative coalition formation. The proposed game includes a mechanism for forming a coalition structure and has two outcomes: the distribution of players among coalitions and payoffs for each player. An individual strategy is a tuple, a coalition structure and a strategy for it. The player has a set of strategies for each coalition structure. Coalition structures are described by Young diagrams. The (social) mechanism transforms the set of all individual strategies into a final one with an explicit distribution of players among coalitions. This mechanism has a coercive force to eliminate conflicts of individual choice. The final coalition structure has a set of individual payoffs. As usual, every game has a mixed strategy equilibrium, which is different from the results of cooperative game theory. The Nash game is a special case of the presented model. We demonstrate how to construct a noncooperative stability criterion for a strong Nash equilibrium.

17.05.2023 [online] Using Kas-seq to identify flipons

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Speakers: Konovalov Dmitry, trainee researcher

The report discusses the results of the analysis of the Kas-seq experiment performed for several human and mouse cell lines. This method allows, using ketoxal, to identify sections of single-stranded DNA. Such areas are formed and often signal the presence of flipons. Special attention was paid to areas in promoter regions. The results of computational experiments show that Kas-seq is consistent with other experimental data and predictions of machine learning models for identifying flipons.

21.06.2023 [online] Development of a pipeline for Z-RNA research

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Speakers: Danilova Anna, research intern

When studying the role of Z-RNA in the functioning of the genome, it is necessary to analyze the secondary structure of RNA. Both the structure itself and the ZH-score value are of interest. Since it is necessary to consider various structures, manual search using ready-made solutions (for example, RNA-Fold) is time-consuming. In addition, existing packages do not allow calculating ZH-score. In this regard, there was a need to develop our own pipeline that would allow us to find various secondary structures for given input sequences, calculate the ZH-score of the resulting structures and visualize them. During the report, the work of the developed pipeline was demonstrated.

19.07.2023 [online] Plasma B cell-associated gene signature predicts better response to immunotherapy in metastatic but not primary melanoma tumors

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Speakers: Puzanov Grigory, researcher

In recent years, a number of studies have pointed to a role for B cells in predicting response to immunotherapy. However, this role varies depending on the tumor type. The report describes the signature of plasma B cells found through analysis of single-cell sequencing data from brain metastases for various tumor types (melanoma, lung cancer, breast cancer, ovarian cancer). For each sample in which B cells were present, a subtype of cells with specific expression of the ZBP1, DERL3 and TNFRSF17 genes was found. The TCGA data further confirms the association of the expression of these genes with plasma cells and reveals an association with better survival for melanoma metastases.

23.08.2023 [online] Mathematical modeling of the spatial structure of protein molecules

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Speakers: Ignatov Andrey Dmitrievich

Modeling the spatial structure of a protein is a computationally complex task associated with a large number of degrees of freedom, and therefore a large number of variables. To simplify this task, large-block models have been proposed to simplify the geometry of the protein molecule. The talk will discuss the large-block HP model based on the hydrophobicity and polarity of protein side chains. Using it, it is possible to reduce the problem of predicting protein conformation to a combinatorial optimization problem, in which the objective function is the number of contacts between H-monomers of the protein chain.

A number of techniques have been proposed to speed up the prediction of the spatial structure of a protein in the HP model. A new precise algorithm has been developed that makes it possible to create both maximally dense hydrophobic nuclei and nuclei with a limitation on the maximum number of contacts between H-monomers. In addition, methods for filtering hydrophobic cores and sets of constraints for placing a protein in a simulated hydrophobic core are proposed.

20.09.2023 [online] Application of machine learning to analyze treatment outcomes for coronary syndrome

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Speaker: Kirdeev Alexander, trainee researcher

The report presents a study aimed at analyzing the effectiveness of treatment for coronary syndrome using various data imputation methods. One of the main aspects of the work is the comparison of data imputation methods, such as IterativeImputer, Missforest, KNN, Mean imputation, in the context of handling missing data in medical datasets. The application and results of each method are reviewed to determine the optimal approach to handling missing values. Additionally, the work analyzes the quality of training using Optuna as an optimizer for selecting hyperparameters. This approach aims to improve model performance and prediction accuracy in the context of coronary syndrome management.

18.10.2023 [online] Biomarkers study to improve Machine Learning prediction of long-term risk of myocardial infarction, stroke, and cardiac death

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Speaker: Konstantin Burkin, research researcher

Currently, cardiovascular diseases occupy 1st place in the number of deaths per capita. A reduction in this indicator can be achieved through early diagnosis of patients. Improving such diagnostics is an important goal and is feasible through the use of biomarker data. The report shows comparison of a number of biomarkers and proves that the use of the PCSK9 biomarker allows a patient's risk to be assessed with high accuracy.

22.11.2023 [online] Study of biomarkers in the diagnosis and prognosis of treatment outcomes for coronary syndrome

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Speaker: Kirdeev Alexander, trainee researcher

The study provides an in-depth analysis of the importance of biomarkers, including NtProBnP and PCSK9, to identify their role in predicting treatment outcomes. The influence of the GRACE 2 integral scale on predicting and assessing the severity of coronary syndrome in the Russian population is also considered. The report not only highlights the importance of biomarkers in medical research, but also provides a comparative analysis of modern Automl solutions, highlighting the unique features of our development pipeline, tailored to the specifics of biomarker analysis in the context of coronary syndromes.


 

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