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Laboratory for Statistical Multi-omics and Bio-informatics

Contract number
075-15-2021-595
Time span of the project
2021-2023
Invited researcher
33
Number of staff members
22
scientific publications
3
Objects of intellectual property
General information

Name of the project: The development of high-performance computational tools for the complex analysis of multi-omics data and the evolvement of personalised medicine

Goals and objectives

The project is aimed at the development of high-productivity computational tools for complex analysis of multi-omics data and the development of personalised medicine. To achieve this, we a planning to create a laboratory for statistical multi-omics at the Institute of Biochemistry and Genetics of the Ufa Federal Research Centre of the Russian Academy of Sciences (IBG UFRC RAS). A high-performance computing cluster and an open online platform for data collection and analysis will also be created. The research will be conducted using existing biological samples and phenotypic data of the IBG UFRC RAS that is a centre for deposition and storage of unique gene banks of the DNAs of   aboriginal inhabitants of various regions of Russia as well as of patients with various diseases and their family members.

We are also planning to expand the biological collection of the IBG UFRC RAS by adding of a deeply phenotyped set. Additionally, the laboratory is planning to conduct a full-genome genotyping for the study of the molecular mechanisms underlying the formation of complex characteristics, including cardiometabolic features, the individual psychological profile (inclination to aggressive behaviour and depression), and sporting characteristics.

To this end, we will use methods of multi-phenotype analysis that were developed under the supervision of Inga Prokopenko and tested using major databases of genotype and clinical data, such as «UK Biobank».

Escala-Garcia M., Canisius S., Keeman R., …., Bermisheva M.,… Khusnutdinova E., … Bachelot T., Schmidt M. K., kConFab A. I.
Germline variants and breast cancer survival in patients with distant metastases at primary breast cancer diagnosis // Scientific Reports. ‒ 2021. ‒ T. 11, № 1. ‒ C. 19787. doi: 10.1038/s41598-021-99409-3.
Korytina G. F., Aznabaeva Y. G., Akhmadishina L. Z., Kochetova O. V., Nasibullin T. R., Zagidullin N. S., Zagidullin S. Z., Viktorova T. V.
The relationship between chemokine and chemokine receptor genes polymorphisms and chronic obstructive pulmonary disease susceptibility in Tatar population from Russia: a case control study // Biochemical Genetics. ‒ 2021.10.1007/s10528-021-10087-2. doi: 10.1007/s10528-021-10087-2.
Timasheva Y., Badykov M., Akhmadishina L., Nasibullin T., Badykova E., Pushkareva A., Plechev V., Sagitov I., Zagidullin N.
Genetic predictors of sick sinus syndrome // Molecular Biology Reports. ‒ 2021. ‒ V. 48, № 6. ‒ P. 5355-5362. doi: 10.1007/s11033-021-06517-4.
Balkhiyarova Z, Luciano R, Kaakinen M, Ulrich A, Shmeliov A, Bianchi M, Chioma L, Dallapiccola B, Prokopenko I, Manco M.
Relationship between glucose homeostasis and obesity in early life—a study of Italian children and adolescents // Human molecular genetics. – 2022. – V. 31(5). – P. 816-26. doi: 10.1093/hmg/ddab287.
Dorling L, Carvalho S, Allen J, ... Bermisheva M, Khusnutdinova E, et al.
Breast cancer risks associated with missense variants in breast cancer susceptibility genes // Genome Med. 2022. – V. 14(1):51. doi: 10.1186/s13073-022-01052-8.
Timasheva Y, Nasibullin TR, Tuktarova IA, Erdman VV, Galiullin TR, Zaplakhova OV, Bakhtiiarova KZ.
Multilocus evaluation of genetic predictors of multiple sclerosiss // Gene. – 2022. Jan 30. 809:146008.
Korytina G. F., Aznabaeva Y.G , Akhmadishina L.Z., Kochetova O.V., Nasibullin T.R., Zagidullin N. Sh., Zagidullin Sh. Z., Viktorova T.V.
The relationship between chemokine and chemokine receptor genes polymorphisms and chronic obstructive pulmonary disease susceptibility in Tatar population from Russia: а case control study // Biochemical Genetics. – 2022. – V. 60. P. 54–79 https://doi.org/10.1007/s10528-021-10087-2.
Yalaev B, Tyurin A, Prokopenko I, Karunas A, Khusnutdinova E, Khusainova R.
Using a Polygenic Score to Predict the Risk of Developing Primary Osteoporosis // Int J Mol Sci. - 2022. - V. 23(17). - P. 10021. doi: 10.3390/ijms231710021.
Ivanova E., Gilyazova I., Pavlov V., Izmailov A., Gimalova G., Karunas A., Prokopenko I., Khusnutdinova E.
MicroRNA Processing Pathway-Based Polygenic Score for Clear Cell Renal Cell Carcinoma in the Volga-Ural Region Populations of Eurasian Continent // Genes. – 2022. - V.13. - P.1281. https:// doi.org/10.3390/genes13071281.
Gilyazova I, Ivanova E, Sinelnikov M, Pavlov V, Khusnutdinova E, Gareev I, Beilerli A, Mikhaleva L, Liang Y.
The potential of miR-153 as aggressive prostate cancer biomarker // Noncoding RNA Res. – 2022. – V. 8(1). - P. 53-59. doi: 10.1016/j.ncrna.2022.10.002.
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