Nikolay Chekanov

ORCID: 0000-0003-1131-3195
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About
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Research Areas
  • Genomics and Phylogenetic Studies
  • RNA and protein synthesis mechanisms
  • RNA modifications and cancer
  • Epigenetics and DNA Methylation
  • Machine Learning in Bioinformatics
  • Trace Elements in Health
  • Genetic Associations and Epidemiology
  • Health, Environment, Cognitive Aging
  • Genetic diversity and population structure
  • Hemoglobinopathies and Related Disorders
  • Cell Image Analysis Techniques
  • Environmental and Industrial Safety
  • Natural Language Processing Techniques
  • Genetics, Bioinformatics, and Biomedical Research
  • Cancer Genomics and Diagnostics
  • Chromosomal and Genetic Variations
  • Arctic and Russian Policy Studies
  • Genomics and Chromatin Dynamics
  • Nutrition, Genetics, and Disease
  • Iron Metabolism and Disorders
  • Process Optimization and Integration
  • Renal and related cancers
  • Genomics and Rare Diseases
  • Yersinia bacterium, plague, ectoparasites research
  • Forensic and Genetic Research

Kharkiv State University of Food Technology and Trade
2019

Russian Academy of Sciences
2009-2017

Federal Center Research Fundamentals of Biotechnology
2017

Pranalytica (United States)
2016

Bioengineering Center
2009-2010

Abstract Recent advancements in genomics, propelled by artificial intelligence, have unlocked unprecedented capabilities interpreting genomic sequences, mitigating the need for exhaustive experimental analysis of complex, intertwined molecular processes inherent DNA function. A significant challenge, however, resides accurately decoding which inherently involves comprehending rich contextual information dispersed across thousands nucleotides. To address this need, we introduce GENA language...

10.1093/nar/gkae1310 article EN cc-by-nc Nucleic Acids Research 2025-01-11
Mark P. Purdue Mattias Johansson Diana Zélénika Jorge R. Toro Ghislaine Scélo and 95 more Lee E. Moore Egor Prokhortchouk Xifeng Wu Lambertus A. Kiemeney Valérie Gaborieau Kevin B. Jacobs Wong‐Ho Chow Давид Заридзе В. Б. Матвеев Jan Lubiński Joanna Trubicka Neonila Szeszenia‐Dąbrowska Jolanta Lissowska Péter Rudnai Eleonóra Fabiánová Alexandru Bucur Vladimír Bencko Lenka Foretová Vladimí­r Janout Paolo Boffetta Joanne S. Colt Faith G. Davis Kendra Schwartz Rosamonde E. Banks Peter J. Selby Patricia Harnden Christine D. Berg Ann W. Hsing Robert L. Grubb Heiner Boeing Paolo Vineis Françoise Clavel-Chapelon Domenico Palli ­Rosario ­Tumino Vittorio Krogh Salvatore Panico Eric J. Duell J. Ramón Quirós María‐José Sánchez Carmen Navarro Eva Ardanáz Miren Dorronsoro Kay‐Tee Khaw Naomi E. Allen H. Bas Bueno-de-Mesquita Petra H. Peeters Dimitrios Trichopoulos Jakob Linseisen Börje Ljungberg Kim Overvad Anne Tjønneland Isabelle Romieu Elio Ríboli Anush Mukeria Oxana Shangina Victoria L. Stevens Michael J. Thun W. Ryan Diver Susan M. Gapstur Paul D.P. Pharoah Douglas F. Easton Demetrius Albanes Stephanie J. Weinstein Jarmo Virtamo Lars J. Vatten Kristian Hveem Inger Njølstad Grethe S. Tell Camilla Stoltenberg Rajiv Kumar Kvetoslava Koppová Olivier Cussenot Simone Benhamou Egbert Oosterwijk Sita H. Vermeulen Katja K.H. Aben Saskia L. van der Marel Yuanqing Ye Christopher G. Wood Pu Xia Alexander M. Mazur Eugenia Boulygina Nikolay Chekanov Mario Foglio Doris Lechner Marta Gut Simon Heath Hélène Blanché Amy Hutchinson Gilles Thomas Zhaoming Wang Meredith Yeager Joseph F. Fraumeni K. G. Skryabin James McKay

10.1038/ng.723 article EN Nature Genetics 2010-12-05

Recent advancements in genomics, propelled by artificial intelligence, have unlocked unprecedented capabilities interpreting genomic sequences, mitigating the need for exhaustive experimental analysis of complex, intertwined molecular processes inherent DNA function. A significant challenge, however, resides accurately decoding which inherently involves comprehending rich contextual information dispersed across thousands nucleotides. To address this need, we introduce GENA-LM, a suite...

10.1101/2023.06.12.544594 preprint EN cc-by-nc-nd bioRxiv (Cold Spring Harbor Laboratory) 2023-06-13

The history of human populations occupying the plains and mountain ridges separating Europe from Asia has been eventful, as these natural obstacles were crossed westward by multiple waves Turkic Uralic-speaking migrants well eastward Europeans. Unfortunately, material records this region are not dense enough to reconstruct details population history. These considerations stimulate growing interest obtain a genetic picture demographic migrations admixture in Northern Eurasia. We genotyped...

10.1186/s12863-017-0578-3 article EN cc-by BMC Genomic Data 2017-12-01

The three epidemiologically important Opisthorchiidae liver flukes Opisthorchis felineus, O. viverrini, and Clonorchis sinensis, are believed to harbour similar potencies provoke hepatobiliary diseases in their definitive hosts, although populations have substantially different ecogeographical aspects including habitat, preferred population structure. Lack of felineus genomic data is an obstacle the development comparative molecular biological approaches necessary obtain new knowledge about...

10.1186/s12864-019-5752-8 article EN cc-by BMC Genomics 2019-05-22

Mammalian forms of the transcription repressor, Kaiso, can reportedly bind methylated DNA and non-methylated CTGCNA motifs. Here we compare DNA-binding properties Kaiso from frog, fish chicken demonstrate that only methyl-CpG-binding function is evolutionarily conserved. We present several independent experimental lines evidence phenotypic abnormalities associated with xKaiso-depleted Xenopus laevis embryos are putative CTGCNA-dependent xKaiso. Our analysis suggests xKaiso does not play a...

10.1242/dev.025569 article EN Development 2009-01-22

Comorbidity or a combination of several diseases in the same individual is common and widely investigated phenomenon. However, genetic background for non-random disease combinations not fully understood. Modern technologies approaches to genomic data analysis enable investigation profile patients burdened with (polypathia, conglomerates) its comparison profiles single diseases. An association study featuring three groups various cardiovascular disorders control group relatively healthy...

10.32607/20758251-2015-7-3-89-99 article EN Acta Naturae 2015-09-15

Abstract An increasing number of studies emphasize the role non-coding variants in development hereditary diseases. However, interpretation such clinical genetic testing still remains a critical challenge due to poor knowledge their pathogenicity mechanisms. It was previously shown that 5′-untranslated regions (5′UTRs) can lead diseases disruption upstream open reading frames (uORFs). Here, we performed manual annotation translation initiation sites (TISs) human disease-associated genes from...

10.1093/nar/gkac1247 article EN cc-by Nucleic Acids Research 2023-01-18

Abstract Interpretation of noncoding genomic variants is one the most important challenges in human genetics. Machine learning methods have emerged recently as a powerful tool to solve this problem. State-of-the-art approaches allow prediction transcriptional and epigenetic effects caused by mutations. However, these require specific experimental data for training cannot generalize across cell types where required features were not experimentally measured. We show here that available...

10.1093/gigascience/giad015 article EN cc-by GigaScience 2023-01-01

At present, the new technologies of DNA sequencing are rapidly developing allowing quick and efficient characterisation organisms at level genome structure. In this study, whole a human (Russian man) was performed using two currently present on market - Sequencing by Oligonucleotide Ligation Detection (SOLiD™) (Applied Biosystems) molecular clusters fluorescently labeled precursors (Illumina). The total number generated data resulted in 108.3 billion base pairs (60.2 from Illumina technology...

10.32607/20758251-2009-1-3-102-107 article EN Acta Naturae 2009-12-15

We report a family case of type II early-onset Alzheimer's disease (AD) inherited over three generations. None the patients in had mutations genes believed to be major risk factors for AD, such as APP, presenilin 1 or 2. Targeted exome sequencing 249 that were previously reported associated with AD revealed rare mutation hemochromatosis (HFE) gene known hemochromotosis. Compared previous studies, we show HFE can possess transferrin-, APOE- and APP-normal patients.

10.1038/hgv.2014.4 article EN cc-by-nc-nd Human Genome Variation 2014-07-31

<ns4:p>Concerns of traditional prenatal aneuploidy testing methods, such as low accuracy noninvasive and health risks associated with invasive procedures, were overcome the introduction novel methods based on genetics (NIPT). These rapidly adopted into clinical practice in many countries after a series successful trials various independent submethods.</ns4:p><ns4:p> Here we present results own NIPT trial carried out Moscow, Russia. 1012 samples subjected to method aimed at measuring...

10.12688/f1000research.8243.1 preprint EN cc-by F1000Research 2016-04-22

At present, the new technologies of DNA sequencing are rapidly developing allowing quick and efficient characterisation organisms at level genome structure. In this study, whole a human (Russian man) was performed using two currently present on market - Sequencing by Oligonucleotide Ligation Detection (SOLiDTM) (Applied Biosystems) molecular clusters fluorescently labeled precursors (Illumina). The total number generated data resulted in 108.3 billion base pairs (60.2 from Illumina...

10.32607/actanaturae.10789 article EN cc-by-nc-nd Acta Naturae 2009-12-15

A somatic cell genome was recently resequenced for a patient with renal cancer. The data were submitted to the NCBI Sequence Read Archive under accession number SRA012240. Here, we have performed SNP calling and compared it several published genomes. We found 2, 921, 724 SNPs, including 1, 472, 679 newly described ones. Among them, 63, 462 SNPs been mapped Y chromosome and, based on 18 markers, has ascribed R1a1a haplogroup predominant in Russian males. mitochondrial determined as U5a, which...

10.32607/20758251-2010-2-3-122-126 article EN Acta Naturae 2010-09-15

Abstract Interpretation of non-coding genomic variants is one the most important challenges in human genetics. Machine learning methods have emerged recently as a powerful tool to solve this problem. State-of-the-art approaches allow prediction transcriptional and epigenetic effects caused by mutations. However, these require specific experimental data for training can not generalize across cell types where required features were experimentally measured. We show here that available...

10.1101/2021.12.31.474623 preprint EN cc-by-nc-nd bioRxiv (Cold Spring Harbor Laboratory) 2022-01-01

The need to find solutions problems on the efficient use of energy resources has been substantiated, under conditions for meeting requirements environmental sustainability production in process executing such technological operations as vaporization and rectification. We have identified prospects searching applying induced processes, which are characterized by high efficiency environmentally friendly.The kinetics temperature investigated effect from heat transfer components internal...

10.15587/1729-4061.2019.180078 article EN Eastern-European Journal of Enterprise Technologies 2019-10-08
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