Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Integrated Computer Analysis of Genomic Sequencing Data Based on ICGenomics Tool. / Orlov, Yuriy L.; Bragin, Anatoly O.; Babenko, Roman O. et al.
Advances in Intelligent Systems, Computer Science and Digital Economics, CSDEIS 2019. ed. / Zhengbing Hu; Sergey Petoukhov; Matthew He. Springer Gabler, 2020. p. 154-164 (Advances in Intelligent Systems and Computing; Vol. 1127 AISC).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
}
TY - GEN
T1 - Integrated Computer Analysis of Genomic Sequencing Data Based on ICGenomics Tool
AU - Orlov, Yuriy L.
AU - Bragin, Anatoly O.
AU - Babenko, Roman O.
AU - Dresvyannikova, Alina E.
AU - Kovalev, Sergey S.
AU - Shaderkin, Igor A.
AU - Orlova, Nina G.
AU - Naumenko, Fedor M.
N1 - Publisher Copyright: © 2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/1/24
Y1 - 2020/1/24
N2 - Fast growth of sequencing data volume demands development of new program systems for processing, storage and analysis of sequencing data. Here we review approaches for data bioinformatics integration using complementary approaches in genomics, proteomics and supercomputer calculations on example of ICGenomics tool. The program complex ICGenomics has been designed previously in Novosibirsk for storage, mining, and analysis of genomic sequences. This tool enables wet-lab biologists to perform high-quality processing of sequencing data in the fields of genomics, biomedicine, and biotechnology. Overall, integrated software tools have to include novel methods of the processing of initial high-throughput sequencing data including gene expression data. Examples of the application areas are: ChIP-seq analysis; functional annotation of gene regulatory regions in nucleotide sequences; prediction of nucleosome positioning; and structural and functional annotation of proteins, including prediction of their allergenicity parameters, as well as estimates of evolution changes in protein families. Applications of the ICGenomics to the analysis of genomic sequences in model genomes are shown. We conclude the presentation by on machine learning methods adaptation in bioinformatics. The ICGenomics tool is available at http://www-bionet.sscc.ru/icgenomics/.
AB - Fast growth of sequencing data volume demands development of new program systems for processing, storage and analysis of sequencing data. Here we review approaches for data bioinformatics integration using complementary approaches in genomics, proteomics and supercomputer calculations on example of ICGenomics tool. The program complex ICGenomics has been designed previously in Novosibirsk for storage, mining, and analysis of genomic sequences. This tool enables wet-lab biologists to perform high-quality processing of sequencing data in the fields of genomics, biomedicine, and biotechnology. Overall, integrated software tools have to include novel methods of the processing of initial high-throughput sequencing data including gene expression data. Examples of the application areas are: ChIP-seq analysis; functional annotation of gene regulatory regions in nucleotide sequences; prediction of nucleosome positioning; and structural and functional annotation of proteins, including prediction of their allergenicity parameters, as well as estimates of evolution changes in protein families. Applications of the ICGenomics to the analysis of genomic sequences in model genomes are shown. We conclude the presentation by on machine learning methods adaptation in bioinformatics. The ICGenomics tool is available at http://www-bionet.sscc.ru/icgenomics/.
KW - Biomedicine
KW - Biotechnology
KW - Genomic sequencing data
KW - ICGenomics
KW - Integrated computer analysis
UR - http://www.scopus.com/inward/record.url?scp=85079087964&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-39216-1_15
DO - 10.1007/978-3-030-39216-1_15
M3 - Conference contribution
AN - SCOPUS:85079087964
SN - 9783030392154
T3 - Advances in Intelligent Systems and Computing
SP - 154
EP - 164
BT - Advances in Intelligent Systems, Computer Science and Digital Economics, CSDEIS 2019
A2 - Hu, Zhengbing
A2 - Petoukhov, Sergey
A2 - He, Matthew
PB - Springer Gabler
T2 - International Symposium on Computer Science, Digital Economy and Intelligent Systems, CSDEIS 2019
Y2 - 4 October 2019 through 6 October 2019
ER -
ID: 23395062