• Developed and implemented an algorithm for CNV

interpretation, which takes into account 3 more

significant parameters than competing algorithms

(Zelenova M. A. et al. Laundering CNV data for

candidate process prioritization in brain disorders

//Molecular Cytogenetics. - 2019. - T. 12. - No. 1. - S. 1-

6.).

• Designed and maintained multiple databases

containing experimental results (up to 1000 samples;

.csv, sqlite, MS Word, depending on a project).

• Authored more than 100 articles and abstracts.
• Presented research data at various conferences, both

as a speaker and a poster presenter, more than 20

times.

• Regularly analyzed large volumes of data (filtering,

processing, interpreting) for different projects (e.g.

various brain disorders, miscarriages, heart disorders)

• Worked with third party databases (obtaining

information, including it in internal bases)

• Participated in the design, conduct, and

manuscript writing of a research dedicated to the

analysis of SARS-CoV-2 genomes.

Stack:

• Data analysis and ML: Python3 (pandas, numpy,

matplotlib, seaborn, plotly, sklearn), SQL (MySQL,

SQLite), Excel/Numbers

• Bioinformatics: genetic databases (OMIM, NCBI, UCSC

genome browser, KEGG, Gene Ontology), tools for NGS

analysis (Samtools, Bedtools, Bowtie 2, vcftools, FastQC,

Galaxy browser), tools for microarray data analysis

(ChAS, DEVA software)

• Data visualisation: Power Point / Keynote, Python3

(matplotib), Cytoscape (Genemania), string.db

• Workflow: Trello, Jira
• Languages: English BIOINFORMATICIAN (C2), German (B1)

Hackathons: winner of a 2021 Glowbyte hackathon (tool for

analysis and aggregation of data of different structure),

winner of a 2022 leadersofdigital.ru hackathon (finding

abnormalities in databases)

Science communication: popular science blog about

genetics @dr_m.green, lectures, TV appearance, articles