Research Advances in Whole-Genome/Exome Sequencing (WGS/WES) and Next-Generation Sequencing
A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Genetics and Genomics".
Deadline for manuscript submissions: closed (30 May 2024) | Viewed by 2202
Special Issue Editor
Interests: next-generation sequencing; third-generation sequencing; variant classification models; inherited disease; single-cell sequencing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Most inherited diseases form a clinically and genetically heterogeneous group of disorders, which generally manifests in many tissues or organs, causing irreversible progressing disease, e.g., cancer, systemic disease, and age-related disease. However, the use of next-generation sequencing such as whole-exome and whole-genome sequencing has improved the diagnostic yield in the search for disease-causing variants in inherited diseases. Still, many genetically inherited diseases remain little-understood, and more research needs to be carried out to unravel these pathophysiological mechanisms. In current standard bulk analyses on DNA genomics or RNA whole-transcriptomics technologies, biologically relevant pathophysiology differences are not always picked up on. However, new technologies, such as long-read sequencing, are being developed for complex bioinformatic analyses in organs, tissue, or even cells, offering the possibility of determining the whole transcriptome, or whole genome, and also the complete epigenome sequence in less than a day. This opens up a fast treatment strategy in translational science.
This Special Issue aims to provide a current overview of advanced research on whole-genome/exome sequencing (WGS/WES) and next-generation sequencing. Reviews and research papers are encouraged on relevant topics.
Dr. Rick Kamps
Guest Editor
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Keywords
- short/long-read sequencing
- whole-exome sequencing
- whole-genome sequencing
- bioinformatics
- variant classification models
- translational medicine
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