Advances in Next-Generation Sequencing for Aging and Cancer Research
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: 28 April 2026 | Viewed by 5
Special Issue Editor
Interests: next-generation sequencing; single-cell sequencing; cellular senescence; aging; cancer genomics; biomarker discovery; precision medicine
Special Issue Information
Dear Colleagues,
Next-generation sequencing (NGS) technologies have revolutionized biomedical research, offering unprecedented resolution and throughput to decode the molecular mechanisms underlying aging and cancer. This Special Issue focuses on the latest advancements in NGS applications that illuminate the complex interplay between genomic, transcriptomic, and epigenomic alterations in aging tissues and cancerous cells. By enabling high-resolution profiling of somatic mutations, gene expression dynamics, and epigenetic modifications, NGS provides critical insights into cellular senescence, tumor evolution, clonal heterogeneity, and age-related disease progression. The integration of bulk and single-cell sequencing, long-read technologies, and multi-omics approaches is transforming our understanding of how aging influences cancer susceptibility and how cancer disrupts normal aging processes. We welcome contributions that explore novel NGS-based methodologies, bioinformatics pipelines, and translational applications in aging and oncology. Studies leveraging NGS to identify biomarkers, therapeutic targets, or mechanisms of resistance in age-associated cancers are particularly encouraged. This Special Issue aims to bridge the gap between aging biology and cancer genomics, fostering interdisciplinary research that advances precision medicine and healthy aging.
Dr. Hyunsoo Kim
Guest Editor
Manuscript Submission Information
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Keywords
- next-generation sequencing
- aging
- cancer genomics
- cellular senescence
- single-cell sequencing
- epigenomics
- transcriptomics
- tumor evolution
- biomarkers
- precision medicine
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