Genetic Advances and Challenges in Complex Diseases
A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Human Genomics and Genetic Diseases".
Deadline for manuscript submissions: 15 November 2024 | Viewed by 199
Special Issue Editor
2. Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD, USA
Interests: computational biology; cardiovascular diseases; age-related diseases; multi-omics; genetics; epigenetics; eQTL; network biology
Special Issue Information
Dear Colleagues,
Advances in genetic and genomic technologies have enabled the acquisition of multi-dimensional high-throughput data from both disease subjects and general populations. These advancements present new challenges and opportunities in developing and applying efficient methods to integrate diverse data types, ultimately revealing novel molecular mechanisms of complex human diseases.
This research topic focuses on advances and challenges in genetic and genomic studies of complex human diseases. We welcome all types of manuscripts, including original basic science research, review articles, methodology papers, translational research, and clinical studies. Topics of interest for this Special Issue include, but are not limited to, the following:
- Next-generation sequencing, including targeted sequencing and whole-genome/exome sequencing analysis for complex human diseases and traits;
- Multi-omics analysis (e.g., transcriptome, epigenome, proteome) of complex human diseases and traits;
- Genetic and genomic association analysis and mendelian randomization analysis utilizing publicly funded big data resources, such as UK Biobank data;
- Discovery of new common and rare variants of human diseases;
- Functional studies to elucidate the molecular mechanisms of newly discovered or previously reported candidate genetic variants identified through genetic association studies;
- New methods for data sharing, harmonization, and analytical approaches for integrating different data types;
- Research using cutting-edge techniques, including single-cell sequencing methods.
Dr. Tianxiao Huan
Guest Editor
Manuscript Submission Information
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Keywords
- genetics
- omics
- multi-omics
- whole-genome sequencing
- whole-exome sequencing
- RNA-sequencing
- GWAS
- mendelian randomization
- methylation
- metabolites
- proteomics
- network
- machine learning
- deep learning
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