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COMPUTER ANALYSIS OF GENE ALTERNATIVE SPLICING IN GLIOMA CELL CULTURES BY RNA-seq DATA

https://doi.org/10.25205/1818-7900-2018-16-3-22-36

Abstract

Fundamental biomedical research in oncology, the search for new markers of tumor development, modern post-genomic studies of gene expression on cell cultures need glioma transcriptome profiling and analysis of individual gene isoforms. Such experiments, in turn, require development of new computer tools and database for analysis of bulk sequencing data. The aim of our study is a computer search for genes and gene isoforms, the difference of their expression is associated with the development of glioblastoma. The work is based on modern high-throughput sequencing technologies and international biomedical data banks analysis. The search for candidate genes in tumors for therapeutic treatment, including individual gene isoforms, is very relevant in healthcare and modern high-tech medicine. This work presents the bioinformatics problems related to the development of computer pipelines for the processing of transcriptomic data, the revealing of the differentially expressed genes, the analysis of alternative splicing, and the description of the gene ontologies categories for the genes sets found. The tasks of automatic search and description of gene functions in connection with cancer diseases, visualization of results and development of biomedical databases are considered. A prototype database of differential alternative splicing of genes is presented, «Differential Alternative Splicing of Human Genes in Secondary Glioblastoma (DASGG)», with the ability to work through a website, to search for expression levels of individual isoforms in tumor cells.

About the Authors

S. S. Kovalev
Novosibirsk State Medical University
Russian Federation


E. Yu. Lieberfarb
Novosibirsk State Medical University
Russian Federation


N. V. Gubanova
Институт цитологии и генетики СО РАН
Russian Federation


A. O. Bragin
Институт цитологии и генетики СО РАН
Russian Federation


A. G. Galieva
Institute of Cytology and Genetics SB RAS; Novosibirsk State University
Russian Federation


A. V. Tsukanov
Novosibirsk State University
Russian Federation


V. N. Babenko
Novosibirsk State University
Russian Federation


Yu. L. Orlov
Novosibirsk State University
Russian Federation


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Review

For citations:


Kovalev S.S., Lieberfarb E.Yu., Gubanova N.V., Bragin A.O., Galieva A.G., Tsukanov A.V., Babenko V.N., Orlov Yu.L. COMPUTER ANALYSIS OF GENE ALTERNATIVE SPLICING IN GLIOMA CELL CULTURES BY RNA-seq DATA. Vestnik NSU. Series: Information Technologies. 2018;16(3):22-36. (In Russ.) https://doi.org/10.25205/1818-7900-2018-16-3-22-36

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