Discoveries in Sequencing Data Analysis
A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Bioinformatics".
Deadline for manuscript submissions: closed (20 December 2022) | Viewed by 6627
Special Issue Editors
Interests: bioinformatics; high-throughput sequencing
Special Issues, Collections and Topics in MDPI journals
Interests: cancer biology; bioinformatics; multi-omics; autoimmune
Special Issue Information
Dear Colleagues,
High-throughput sequencing has been widely used in functional genomics studies and has revolutionized biological sciences. It enables researchers to perform a wide range of investigations and to study biological systems at an unprecedented level, as exemplified by large international research projects, including The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression project (GTEx), which provided comprehensive multi-omics sequencing datasets for research by scientists across the world. Analysis of sequencing data converts sequence information into meaningful knowledge and insights, which involves algorithm development, annotation or cataloguing information, multi-omics data integration, biomarker and drug target discovery, and disease diagnosis and drug response prediction. Whole transcriptome sequencing (RNA-seq), for example, provides sequence information about coding and multiple noncoding forms of RNA to assess variations and gene expression levels across the entire genome. Varied information can be obtained from RNA-seq, including gene expression levels, alternative splicing (AS), alternative polyadenylation (APA), gene fusion, and RNA editing. For genome or exome sequencing, nucleotide polymorphisms and structural variations, in addition to telomere variations, can be identified to uncover driver genomic events. Furthermore, single-cell RNA or DNA sequencing (scRNA- or scDNA-seq) has dramatically improved our understanding of biology in every aspect. Novel discoveries in sequencing data analysis are critical to pinpoint the key players in pathological conditions, especially for cancer and other age-related diseases.
The aim of this Special Issue is to provide a broad and up-to-date overview of “Discoveries in Sequencing Data Analysis” to elucidate new approaches analyzing sequencing data, integrating multi-omics data, discovering biological mechanisms, and developing novel treatments or therapies for diseases. Contributions in the form of research papers and reviews from experts in the field are needed to improve our understanding of relevant biological issues.
Dr. Yuanyan Xiong
Dr. Mengbiao Guo
Guest Editors
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Keywords
- sequencing data analysis
- multi-omics data integration
- biomarker identification
- drug repurposing and drug response prediction
- discoveries in immunology, cancer, and developmental biology
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