Integration of multi-omics and single-cell resolution
Research gap analysis derived from 3 biology papers in our local library.
The gap
Integration of multi-omics and single-cell resolution to uncover heterogeneity and trajectories in HSC aging. Application of machine learning and deep learning frameworks for predictive modeling and epigenome aging clocks. Exploration of th
Evidence profile
Sourced from the future work and future-work section and stated research gap of the source papers, classified as general, spanning 3 journals.
Research trend
Established — well-defined area with open sub-problems.
Supporting evidence — 3 representative gaps
- Single-cell eQTL-based Mendelian randomization identifies immune cell subtype-specific regulators of epigenetic aging and prioritizes candidate therapeutic targets (2026) · Biogerontology · doi
Single‑cell eQTL‑based Mendelian randomization identifies immune cell subtype‑specific regulators of epigenetic aging and prioritizes candidate therapeutic targets Chun Zhang · Jingqi Zhang Received: 13 March 2026 / Accepted: 16 May 2026 © The Author(s), under exclusive licence to Springer Nature B.V. 2026 Abstract Epigenetic aging clocks offer precise measures of biological age, yet the causal contributions of immune gene expression within specific cell subtypes to epigenetic aging remain poorly understood.
generalfuture workevidence 5/5Keywords: cell epigenetic aging acceleration single eqtl immune specific zhang clocks based mendelian randomization identifies subtype - Hematopoietic stem cell aging: a review of transcriptional and multi-omics insights and potential paths for AI integration (2026) · Experimental & Molecular Medicine · doi
Integration of multi-omics and single-cell resolution to uncover heterogeneity and trajectories in HSC aging. Application of machine learning and deep learning frameworks for predictive modeling and epigenome aging clocks. Exploration of therapeutic interventions for age-related immune decline, anemia, and hematologic malignancies.
generalfuture-work sectionevidence 5/5Keywords: integration multi-omics single-cell resolution uncover heterogeneity trajectories hsc - Single-cell multi-omics dissects transcript isoform and immune repertoire dynamics in human immunosenescence (2026) · Science China Life Sciences · doi
Single-cell RNA sequencing fails to capture deeper regulatory layers, such as transcript isoform diversity and the remodeling of immune receptor repertoires. Conventional gene-level analyses miss a substantial layer of intra-locus heterogeneity. Prior work has not provided a comprehensive atlas of immune aging at single-cell resolution.
generalstated research gapevidence 5/5Keywords: single-cell rna sequencing fails capture deeper regulatory layers
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