High-Throughput Sequencing Data Analysis for Industrial Applications
A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".
Deadline for manuscript submissions: closed (31 January 2024) | Viewed by 9102
Special Issue Editors
Interests: entomology; bioinformatics; genome data analysis; trancriptomics; molecular biology; immunology
Special Issues, Collections and Topics in MDPI journals
2. Genome Editing Innovation Center, Hiroshima University, 3-10-23 Kagamiyama, Higashi-Hiroshima City 739-0046, Japan
3. Database Center for Life Science (DBCLS), Joint Support-Center for Data Science Research, Research Organization of Information and Systems, 1111 Yata, Mishima 411-8540, Shizuoka, Japan
Interests: bioinformatics; biological databases; genome editing; functional genomics; genome sequencing; meta-analysis; transcriptome analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recent high-throughput DNA sequencers have made it possible to generate DNA and RNA sequence data at a low cost and in a short time. They revolutionized biological research. For instance, high-quality genome sequence data or transcriptome data including many samples of model and non-model species, such as insects, fishes and plants, have been available, or the compositions of microorganisms in multiple environments can be revealed (meta-genome analysis). In the future, modified biological resources are expected to be designed by the combination of the analysis of high-throughput nucleotide data and gene modification techniques. This Special Issue will provide an overview of the latest applications of data analysis to biological research, with a main focus on the bio-industries. The aim of this Special Issue is to promote biological research using sequence data analysis for the industrial utilization of new biological resources. Authors are requested to deposit newly sequenced data and to include the accession IDs of the data in the manuscript. Additionally, the analyzed data files (e.g., the expression value table of all transcripts) should be uploaded to public data repositories such as figshare, and the DOI (Digital Object Identifier) of the data should be displayed to ensure the reproducibility of data analysis. Potential topics include, but are not limited to:
- Biological mechanisms at the molecular or genetic level using a non-human model;
- Reference genome and transcriptome data for industry-important model and non-model organisms;
- Ecological reports using high-throughput sequence data;
- Metagenomics in model and non-model organisms and its application to industry;
- Meta-analysis using high-throughput sequence data deposited in a public database (NCBI/ENA/DDBJ);
- Genome editing research for industrial applications using high-throughput sequencing in model and non-model organisms.
Dr. Kakeru Yokoi
Prof. Dr. Hidemasa Bono
Guest Editors
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Keywords
- next-generation sequencer (NGS)
- meta-analysis
- genome analysis
- transcriptome analysis
- metagenome analysis
- genome editing
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