Informatics of Biological Functions (IQB)

Associate Professor: Ryuichiro Nakato
TEL: 03-5841-1471
E-mail: rnakato[at]

[Keywords] Genomics, Next generation sequencer, data-driven analysis, multi-NGS omics

 Genome-wide analyses with Next Generation Sequencer (NGS) is a mainstream method in computational genomics and has led to important discoveries for dynamic regulation of the genome related to diseases, cell differentiation and evolutional conservation. Our group has been trying to develop new tools and analyze various NGS data including ChIP-seq, ATAC-seq, RNA-seq, Exome-seq, Hi-C, ChIA-PET, and Single-cell analysis, to extract important biological information from large-scale datasets (~hundreds of samples), namely “data-driven analysis.” Our aim is to develop a pipeline for multi-NGS omics that integratively analyzes large-scale datasets from multiple NGS assays and achieve an epoch-making discovery, e.g., higher-order coordination of multiple DNA-binding factors. Currently we mainly focus on the ChIP-seq (epigenome), Hi-C (3D genome folding) and single-cell analysis (cellular heterogeneity in tissue samples). We accept students both of biology and of informatics who are interested in bioinformatics.

Research themes:

・ Develop a tool for integrative NGS analysis (e.g., ChIP-seq and Hi-C)
・ Quality assessment, normalization and visualization of NGS data
・ Whole-genome annotation using multiple NGS data
・ Machine-learning method for imputation and noise reduction to refine NGS data
・ Fast and memory-efficient computation for large-scale NGS analysis
・ Collaboration with biology labs: obtain new biological insights from new NGS data
・ Other collaborative themes also available: in-silico simulation of 3D genome (polymer simulation), time-course modeling of single-cell RNA-seq data (systems biology)


The University of Tokyo
Graduate School of Frontier Sciences, The University of Tokyo

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