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 -