Biology subjects

Moskalenko, V.

Publications and source records attributed to Moskalenko, V..

3 recordsLinked to original sources

bioRxiv2024

Use of deep learning algorithms for segmentation of microelectrode arrays electrograms in the study of changes in myocardial bioelectrical activity

The using of modern electrophysiological methods during scientific research implies processing of huge data sets which becomes a significant problem. Progress in the development of equipment for registration of multiple local field potentials from the tissue surface contributes to the study of spatio-temporal characteristics of myocardial bioelectrical activity at a more detailed level. But it also raises the need for automation of data analysis, which can be accomplished by algorithms based on machine learning. New scientific approaches can contribute to the discovery of new facts about substances widely used but with under-researched efficacy. The paper presents the results of epicardial mapping by flexible microelectrode arrays of myocardium of isolated rat heart perfused with a solution containing L-carnitine, nutritional supplement that may be recommended for people suffering from cardiovascular disease. Electrograms from microelectrode arrays were analyzed using a neural network model based on U-Net architecture adapted for segmentation of one-dimensional signal. It was shown that the presence of L-carnitine in the perfusion solution caused a decrease in heart rate, myocardial excitation conduction velocity, coronary blood flow intensity of the isolated rat heart and suppressed physiological responses of the heart to adrenaline stimulation.

physiology↗

bioRxiv2022

Residual DNA in enzymes may pose a challenge for DIY RNA sequencing protocols: how to deal

High-throughput RNA sequencing (RNA-seq) is widely employed for gene expression profiling. This report on do-it-yourself RNA-Seq library preparation pitfalls, highlighting their correct identification and successful overcoming, may be helpful to research groups commencing a DIY RNA-Seq workflow and facing similar problems.

genomics↗

bioRxiv2021

SYSTEM ANALYSIS OF THE SEQUENCING QUALITY OF HUMAN WHOLE EXOME SAMPLES ON BGI NGS PLATFORM

Human whole exome sequencing (WES) is now the standard for most medical genetics applications worldwide. The leaders are manufacturers of enrichment kits that base their protocols on a hybridization approach using cRNA or cDNA biotinylated samples specific to regions of interest in the genome. Recently, platforms from the Chinese company MGI Tech have been successfully promoted in the markets of many countries in Europe and Asia. There is no longer any question about their reliability and the quality of the data obtained. However, very few task-specific kits for WES, in particular, are presented for these sequencers. We have developed our solution for library pre-capture pooling and exome enrichment using Agilent probes. In this work, we demonstrate on a set of standard benchmark samples from the Platinum Genome Collection that our protocol, called "RSMU_exome", is superior to the kit from MGI Tech in qualitative and quantitative terms. It allows detecting more SNVs and CNVs with superior sensitivity and specificity values, generates fewer PCR duplicates, allows more samples to be pooled in a single enrichment, and requires less raw data to produce results comparable to the MGI Tech solution. Also, our protocol is significantly cheaper than the kit from the Chinese manufacturer.

genomics↗