Advancing Applied Microbiology: Integrating Next-Generation and Third-Generation Sequencing Technologies
A special issue of Microorganisms (ISSN 2076-2607). This special issue belongs to the section "Systems Microbiology".
Deadline for manuscript submissions: 30 November 2024 | Viewed by 89
Special Issue Editors
Interests: biomaterials; exopolysaccharides; extremophilic bioprocessing; biocatalysis
Special Issues, Collections and Topics in MDPI journals
Interests: next generation sequencing assay design and validation; development and validation of molecular biology methods; development of custom bioinformatics pipeline for analyzing long read and short read sequencing datasets; microbial and enzymatic processing
Special Issue Information
Dear Colleagues,
The usage of both next-generation (short-read) and third-generation (long-read) sequencing in applied microbiology has brought a new dimension to research and development in industrial applications and environmental monitoring. The usage of these sequencing technologies provides a valuable toolkit for microbial identification, genotyping, and resistance gene mapping. These toolkits can be applicable in diverse fields including health improvement, combating antibiotic resistance, bioprocessing optimization, and environmental sample analysis. While short-read sequencing provides a high throughput, low error rate, and cost effectiveness for microbial community analysis, long-read sequencing excels in characterizing complex genomic regions and fully characterizing microbial genomes. Integrating these technologies enhances our understanding of microbial genetics that will facilitate the development of robust biotechnological processes. Additionally, the advancement of machine learning (ML) algorithms has enabled the sophisticated and large-scale analysis of short- and long-read sequencing datasets, thereby promoting automation and predictive modeling in industrial settings. This Special Issue seeks to gather articles (latest research, reviews, and short communications) that use the aforementioned sequencing technologies to explore fundamental scientific principles. We welcome contributions on topics such as, but not limited to, microbial genomics, novel bioengineering approaches, and innovative ML-driven bioinformatics tools designed to analyze complex sequencing data.
Prof. Dr. Rajesh K. Sani
Dr. Abhilash Kumar Tripathi
Guest Editors
Manuscript Submission Information
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Keywords
- sequencing
- genomics
- transcriptomics
- metagenomics
- bioinformatics
- machine learning
- microbiome
- bioengineering
- microbial identification
- microbial evolution
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