Almaty, Kazakhstan
I am a practicing bioinformatician with two years of experience in both industry and academic research. My work spans NGS (Metagenomics, 16S, nanopore sequencing, single-cell transcriptomics, CNV, microarray scanners, population genetics, ancient DNA, data interpretation) and Structural biology (Molecular Dynamics Simulation). My track record comprises projects in medical genetics and antimicrobial research where I contributed via active use of data-driven approach and pipeline development. Passionate about combining computational tools with biology, I am proactively developing my skills to uncover insights with meaningful impact on human health.
- Developing a deep learning model to predict endocrine therapy sensitivity from pathology images in a neoadjuvant breast cancer trial.
1) Research dedicated to Alzheimer disease genotyping. Responsible for evaluation of SNPs’ significance utilizing statistical methods and interpretation of mutation pathogenesis. Investigated linkage disequilibrium patterns and GO annotations. 2) H12-Based Insights into Genetic Selection. Analyzed ancient and modern Kazakh genomes to detect signals of Natural Selection using H12 and G12 haplotype homozygosity statistics.
- Preimplantation Genetic Testing (PGT) internal platform for clinicians based on microarray and NGS data - Project “Comparative analysis of metagenomic programs for identifying species based on 16S rRNA long-read and short-read data” - Pipeline for shotgun metagenomics data, benchmark of novel classifiers - Implemented pipeline for CNV detection on NGS and microarray scanners - Maintenance of servers and storage infrastructure
- Automative reports for optimization of sequencers’ workload
- Conducted a project investigating post-stroke brain dynamics under inhaled nitric oxide (iNO) treatment using single-cell RNA sequencing analysis in mice model. My responsibilities included data preprocessing, interpretation of cell-type-specific transcriptional programs. - Presented findings at the Amgen Scholars Symposium, University of Cambridge, UK.
- Project focuses on simulation of antimicrobial peptides (AMP) that can self-assemble into antibacterial trap-and-kill nanonets. - I was primary responsible for creating Molecular Dynamics Simulations for membrane-peptides systems and analyzing the resulting trajectories.