TY - JOUR

T1 - Glioblastoma gene network reconstruction and ontology analysis by online bioinformatics tools

AU - Gubanova, Natalya V.

AU - Orlova, Nina G.

AU - Dergilev, Arthur I.

AU - Oparina, Nina Y.

AU - Orlov, Yuriy L.

N1 - The work was supported by the Ministry of Science and Higher Education of the Russian Federation via the Institute of Cytology and Genetics (state budget project No 0259-2021-0014). Publisher Copyright: © 2021 Natalya V. Gubanova et al., published by De Gruyter, Berlin/Boston.

PY - 2021/11/16

Y1 - 2021/11/16

N2 - Glioblastoma is the most aggressive type of brain tumors resistant to a number of antitumor drugs. The problem of therapy and drug treatment course is complicated by extremely high heterogeneity in the benign cell populations, the random arrangement of tumor cells, and polymorphism of their nuclei. The pathogenesis of gliomas needs to be studied using modern cellular technologies, genome- and transcriptome-wide technologies of high-throughput sequencing, analysis of gene expression on microarrays, and methods of modern bioinformatics to find new therapy targets. Functional annotation of genes related to the disease could be retrieved based on genetic databases and cross-validated by integrating complementary experimental data. Gene network reconstruction for a set of genes (proteins) proved to be effective approach to study mechanisms underlying disease progression. We used online bioinformatics tools for annotation of gene list for glioma, reconstruction of gene network and comparative analysis of gene ontology categories. The available tools and the databases for glioblastoma gene analysis are discussed together with the recent progress in this field.

AB - Glioblastoma is the most aggressive type of brain tumors resistant to a number of antitumor drugs. The problem of therapy and drug treatment course is complicated by extremely high heterogeneity in the benign cell populations, the random arrangement of tumor cells, and polymorphism of their nuclei. The pathogenesis of gliomas needs to be studied using modern cellular technologies, genome- and transcriptome-wide technologies of high-throughput sequencing, analysis of gene expression on microarrays, and methods of modern bioinformatics to find new therapy targets. Functional annotation of genes related to the disease could be retrieved based on genetic databases and cross-validated by integrating complementary experimental data. Gene network reconstruction for a set of genes (proteins) proved to be effective approach to study mechanisms underlying disease progression. We used online bioinformatics tools for annotation of gene list for glioma, reconstruction of gene network and comparative analysis of gene ontology categories. The available tools and the databases for glioblastoma gene analysis are discussed together with the recent progress in this field.

KW - drug search

KW - gene networks

KW - gene ontology

KW - glioblastoma

KW - medical genomics

KW - Humans

KW - Computational Biology

KW - Gene Expression Regulation, Neoplastic

KW - Gene Expression Profiling

KW - Brain Neoplasms/genetics

KW - Gene Regulatory Networks

KW - Glioblastoma/genetics

KW - Glioma/genetics

KW - Gene Ontology

UR - http://www.scopus.com/inward/record.url?scp=85123025123&partnerID=8YFLogxK

U2 - 10.1515/jib-2021-0031

DO - 10.1515/jib-2021-0031

M3 - Article

C2 - 34783229

AN - SCOPUS:85123025123

VL - 18

JO - Journal of integrative bioinformatics

JF - Journal of integrative bioinformatics

SN - 1613-4516

IS - 4

ER -