Laboratory for Large-Scale Biomedical Data Technology

Rapid advances in AI-based technologies have highlighted the critical importance of high-quality data. In biomedical research, continuous innovation in experimental and measurement technologies enables the acquisition of diverse biomolecular and biological activity data, resulting in large and heterogeneous datasets. To effectively leverage these data, data engineering methodologies and sustained efforts to curate and maintain data quality are essential.

We have been conducting multiple research projects aimed at developing data resources that support studies of transcriptional regulation (Figure). Transcriptional regulation plays a central role in controlling gene activity and underlies differences among cell types, tissues, and disease states, thereby influencing disease mechanisms, biomarker discovery, and therapeutic target identification. This process involves multiple regulatory layers, including transcriptional activity, transcription factor binding, epigenomic states, and genomic variation. Consequently, understanding transcriptional regulation in biomedical research requires systematic integration and analysis of large-scale, heterogeneous datasets derived from diverse experimental modalities.

Among the data resources developed by our team is SCPortalen2 (https://single-cell.riken.jp/), which provides curated metadata and uniformly reprocessed data files to facilitate reuse of single-cell datasets, including studies of cellular heterogeneity in health and disease. We have also developed refTSS4 (https://reftss.riken.jp/), a reference resource defining transcription start sites (TSSs) across the genome, supporting accurate interpretation of regulatory disruptions associated with genetic diseases. In addition, we are constructing fanta.bio (https://fanta.bio/), a comprehensive atlas of cis-regulatory elements (CREs) that integrates genomic locations, regulatory activities across diverse samples, and associations with genomic variations in human and mouse.

In parallel with these data resource development efforts, our laboratory provides and supports information infrastructure for multiple IMS laboratories, enabling and accelerating large-scale omics studies.

Through these efforts, our laboratory contributes to biomedical research by enabling data-driven investigations into gene regulation, disease mechanisms, and translational applications based on large-scale omics data.