“Kirill has fantastic interpersonal and technical traits. Hard working, passionate, detail-oriented, energetic, charismatic, inquisitive, helpful, open minded, and very friendly. He was always very well liked by everyone I have seen interact with him in the workplace. He was helpful to me and also genuinely interested in my field of work, to broaden his own expertise. Any organization fortunate to work with Kirill will get incredible value by having him on their team. He is very versatile mentally, and in terms of his current capabilities. He will undoubtedly keep making profound contributions to science and technology, and continue to improve people's lives as a result. ”
About
I am a professional specializing in Bioinformatics, Data processing and analytics (clinical, biological) and other Biology-related fields. My wet-lab and in silico expertise spans the fields of Bioinformatics, Pathogen Biology, Data Mining, Structural Biology, Molecular Dynamics.
I am open to data analysis and software development opportunities
Activity
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I am happy to share that I am officially certified Front-end Web Developer! 🎉
I am happy to share that I am officially certified Front-end Web Developer! 🎉
Liked by Kirill (Kyrylo) Bessonov
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It took a while, but I finally got it done! https://lnkd.in/dA-MdMCs
It took a while, but I finally got it done! https://lnkd.in/dA-MdMCs
Liked by Kirill (Kyrylo) Bessonov
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I am very happy the ERC decided to support our team for another 5 years with this INSTant CARMA project. I'm beyond exited to get the work started!…
I am very happy the ERC decided to support our team for another 5 years with this INSTant CARMA project. I'm beyond exited to get the work started!…
Liked by Kirill (Kyrylo) Bessonov
Experience
Education
Volunteer Experience
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Community Volunteer
Центр социальной помощи семье и детям Петродворцового района (Lomonosov)
- Present 8 years 10 months
Social Services
Talked and educated children that recently lost their family or were temporarily were removed from their parents due to dispute or other causes.
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Volunteer (Cancer Unit)
Sunnybrook Health Sciences Centre
- 8 months
Health
Helped staff with administrative duties. Tried to improve emotional state of the patients via personal one on one talks. Participated in ethical training sessions.
Publications
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ECTyper: in silico Escherichia coli serotype and species prediction from raw and assembled whole-genome sequence data
Microbial Genomics
Escherichia coli is a priority foodborne pathogen of public health concern and phenotypic serotyping provides critical information for surveillance and outbreak detection activities. Public health and food safety laboratories are increasingly adopting whole-genome sequencing (WGS) for characterizing pathogens, but it is imperative to maintain serotype designations in order to minimize disruptions to existing public health workflows. Multiple in silico tools have been developed for predicting…
Escherichia coli is a priority foodborne pathogen of public health concern and phenotypic serotyping provides critical information for surveillance and outbreak detection activities. Public health and food safety laboratories are increasingly adopting whole-genome sequencing (WGS) for characterizing pathogens, but it is imperative to maintain serotype designations in order to minimize disruptions to existing public health workflows. Multiple in silico tools have been developed for predicting serotypes from WGS data, including SRST2, SerotypeFinder and EToKi EBEis, but these tools were not designed with the specific requirements of diagnostic laboratories, which include: speciation, input data flexibility (fasta/fastq), quality control information and easily interpretable results. To address these specific requirements, we developed ECTyper (https://github.com/phac-nml/ecoli_serotyping) for performing both speciation within Escherichia and Shigella , and in silico serotype prediction. We compared the serotype prediction performance of each tool on a newly sequenced panel of 185 isolates with confirmed phenotypic serotype information. We found that all tools were highly concordant, with 92–97 % for O-antigens and 98–100 % for H-antigens, and ECTyper having the highest rate of concordance. We extended the benchmarking to a large panel of 6954 publicly available E. coli genomes to assess the performance of the tools on a more diverse dataset. On the public data, there was a considerable drop in concordance, with 75–91 % for O-antigens and 62–90 % for H-antigens, and ECTyper and SerotypeFinder being the most concordant. This study highlights that in silico predictions show high concordance with phenotypic serotyping results, but there are notable differences in tool performance. ECTyper provides highly accurate and sensitive in silico serotype predictions, in addition to speciation, and is designed to be easily incorporated into bioinformatic workflows.
Other authorsSee publication -
Docking and molecular dynamics simulations of the Fyn-SH3 domain with free and phospholipid bilayer-associated 18.5-kDa myelin basic protein (MBP) – Insights into a non-canonical and fuzzy interaction
Proteins: Structure, Function, and Bioinformatics
In this article we provide a clear application example of docking and molecular dynamics approaches to study protein-protein interactions in the context of Multiple Sclerosis (MS) - autoimmune disease of the central nervous system (brain, spinal cord). Article contains an extensive online supplement with MD trajectories and high resolutions figures and pipeline scripts.
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Integration of gene expression and methylation to unravel biological networks in glioblastoma patients
Genetic Epidemiology 41.2 (2017): 136-144.
The vast amount of heterogeneous omics data, encompassing a broad range of biomolecular information, requires novel methods of analysis, including those that integrate the available levels of information. In this work, we describe Regression2Net, a computational approach that is able to integrate gene expression and genomic or methylation data in two steps. First, penalized regressions are used to build Expression-Expression (EEnet) and Expression-Genomic or Expression-Methylation (EMnet)…
The vast amount of heterogeneous omics data, encompassing a broad range of biomolecular information, requires novel methods of analysis, including those that integrate the available levels of information. In this work, we describe Regression2Net, a computational approach that is able to integrate gene expression and genomic or methylation data in two steps. First, penalized regressions are used to build Expression-Expression (EEnet) and Expression-Genomic or Expression-Methylation (EMnet) networks. Second, network theory is used to highlight important communities of genes. When applying our approach, Regression2Net to gene expression and methylation profiles for individuals with glioblastoma multiforme, we identified, respectively, 284 and 447 potentially interesting genes in relation to glioblastoma pathology. These genes showed at least one connection in the integrated networks ANDnet and XORnet derived from aforementioned EEnet and EMnet networks. Although the edges in ANDnet occur in both EEnet and EMnet, the edges in XORnet occur in EMnet but not in EEnet. In-depth biological analysis of connected genes in ANDnet and XORnet revealed genes that are related to energy metabolism, cell cycle control (AATF), immune system response, and several cancer types. Importantly, we observed significant overrepresentation of cancer-related pathways including glioma, especially in the XORnet network, suggesting a nonignorable role of methylation in glioblastoma multiforma. In the ANDnet, we furthermore identified potential glioma suppressor genes ACCN3 and ACCN4 linked to the NBPF1 neuroblastoma breakpoint family, as well as numerous ABC transporter genes (ABCA1, ABCB1) suggesting drug resistance of glioblastoma tumors.
Languages
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English
Native or bilingual proficiency
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Spanish
Full professional proficiency
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French
Professional working proficiency
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Russian
Native or bilingual proficiency
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Ukrainian
Professional working proficiency
Recommendations received
8 people have recommended Kirill (Kyrylo)
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