KZ
RU
LABORATORY OF GENOMIC
AND PERSONALIZED MEDICINE
ABOUT LAB
MEMBERS
EQUIPMENT
ABOUT LAB
MEMBERS
EQUIPMENT
Laboratory of Genomic and Personalized Medicine is focused on development of new approaches of ICA application for analysis and interpretation of tumor heterogeneity, on the study of gene expression and genomic variants in cancer/normal tissues, on analysis of whole genomes/exomes of Kazakh individuals and identification of Kazakh specific genomic variants with developing national genomic reference database, on the study of differential expression in plants in different states and parts, genome organization and genetic variants of drug-resistant M.tuberculosis strains circulating in Kazakhstan, on development of bioinformatics tools implementing a machine learning approaches as applied to DNA detection and amplification technologies as well as development of novel bioinformatics tools and databases.

MAIN RESEARCH AREAS
Studying the genetic architecture of the Kazakh population and other populations of Central Asia using high-throughput genomic platforms to assess the risk of development and prediction of various conditions, creating a reference database.

Investigation of molecular mechanisms of major multifactorial diseases in Kazakhstan (cardiovascular, oncological, metabolic syndrome, neurodegenerative diseases).

Research of tuberculosis and infectious diseases in Kazakhstan: epidemiology, genetics, environmental risk factors, lifestyle, search of new diagnostic biomarkers, host-vector interaction, antibiotic resistance, preventive strategies, studying epidemiology of SARS-CoV2 coronavirus, COVID-19, etc.

Development and implementation of new next-generation (NGS) and third-generation (TGS, nanopore sequencing) sequencing methods and translation of genomic technologies into clinical practice and development of applied genetics in biomedicine, population genetics, sports genetics and agriculture
MEMBERS
  • Ainur Akilzhanova, PhD, DMS
    Professor and Laboratory Head
  • Ulan Kozhamkulov, Ph.D
    A/Professor and Leading Researcher
  • Saule Rakhimova, Ph.D
    A/Professor and Leading Researcher
  • Madina Zhalbinova
    Junior Researcher
  • Dauren Yerezhepov, Ph.D
    Researcher

  • Akbota Aitkulova

    Researcher
EQUIPMENT
Next-generation sequencing platform, TGS Nanopore, long fragments. Oxford Nanopore technologies,PromethION 48, 2020
Sequencing of individual gene segments by the Sanger method
Genetic analyzer 96-capillary
3730xl DNA Analyzer, 2012
Next Generation Sequencing Platform, NGS
Illumina HiSeq2000, 2013
Whole-genome and targeted sequencing
Next Generation Sequencing Platform, NGS
Illumina MiSeq, 2015
Whole-genome and targeted sequencing
Next-generation sequencing platform, TGS Nanopore, long fragments
Oxford Nanopore technologies,PromethION 48, 2020
Whole genome and targeted sequencing. Whole genomes/exomes/transcriptomes
Genetic analyzer 8-capillary
3500 HID Genetic Analyzer, 2015
Sequencing of individual gene segments by fragment analysis
Automatic sample preparation system
PerkinElmer Janus NGS Express, 2015
Preparing libraries for sequencing
Ionalyzer
Bioanalyzer-2100, Agilent technologies, 2012
Fragment analysis of nucleic acids
Microarray analyzer for nucleic acids and proteins
PerkinElmer LabChip Touch 24, 2015
Highly accurate analysis of proteins and nucleic acids
Pectrophotometer
NanoDrop 2000c, 2012
For DNA quantification
CR amplifier
Eppendorf Mastercycler Pro S, 2012
Running a polymerase chain reaction
Real-time quantitative PCR system
7900 Fast Real Time System, Applied Biosystems, 2013
Running Quantitative Real-Time PCR
Gel documentation system
BioRad GelDoc, 2012
Quantitative DNA assessment, gel analysis
Server, high-power computers
Q-symphony, computing systems
Bioinformatics analysis, data storage
High-performance bioinformatics cluster “Q-Symphony”:
Hewlett-Packard Enterprise – Apollo (208 Cores x Intel Xeon, 3.26 TB RAM, 258 ТB RAID HDD, RedHat Linux)
Max computing performance 7.5 TFlops: specifically designed architecture optimized for bioinformatics research and analysis of big genomics datasets (whole-genome/whole transcriptomes datasets and genomics bulk datasets with more than 100 samples simultaneously).
Small bioinformatics cluster Dell PowerEdge Cluster (64 x Cores AMD Opteron, 128 Gb RAM, 20 Tb RAID) – high-performance server capable to perform tasks on analysis of small sample size next-generation sequencing data (human whole-genome, whole-exomes, whole transcriptomes analysis, up to 10 samples simultaneously).
Server Dell T430 (2x Intel Xeon (12 Cores), 64 Gb RAM, 8 Tb RAID, Windows Server) – medium-performance server on Windows platform for developing Windows-based bioinformatics methods and Matlab codes application.
Server HP Z800 (2х Intel Xeon (16 Cores), 48 Gb RAM) – medium-performance server for performing bioinformatics analysis of viral and bacterial genomes.
Synology Storage System (50 Tb Raid) – archiving server for massive storage and biomedical data encryption.