About HGC

Laboratory of DNA Information Analysis

Laboratory of DNA Information Analysis

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Professor: Satoru Miyano
Associate Professor: Seiya Imoto
Assistant Professor: Teppei Shimamura
Technical Specialist: Ayumu Saito

Research activities

The aim of the research at this laboratory is to investigate and develop knowledge information processing systems for knowledge discovery, information interpretation and knowledge bases that deal with biological information about gene expression data, nucleic acid sequences and proteins. The following three topics are mutually allied to pathway and gene networks analyses on computer.

Gene expression profile analysis

For inferring the genetic network from gene expression profile data, various algorithms for analyzing the network are being developed. In particular, we have realized a novel gene network inference method based on Bayesian network and nonparametric regression, a visulalized gene network analysis system together with the knowledge base of the genetic network of organisms, and a clustering software library.

Knowledge discovery system

We have been developing a system Hypotheis Creator (HC) for assisting knowledge discovery from complete genomes, SNP data, gene expression profile data, protein data. With this concept, simultaneously, we have been conducting various computational knowledge dicoveries for protein localization prediction extraction and aberrant splicing.

Modeling and simulation of biopathways

As one of the topics in Systems Biolgy, we have been creating an computational environment for modeling and simulation of biopathways in cells and organisms focused on gene regulatory networks, signaling pathways, metabolic pathways, and physical simulations, etc. With this approach, the functions of genes and systems of genes will be analyzed and predicted. This research is realized as a software Genomic Object Net (http://www.GenomicObject.Net/).

Fig. 1: Inference of gene network based on Bayesian network and nonparametric regression from gene expression profile data and a snapshot of its visualized network analysis sytem. fig2.jpg
Fig. 2: Genomic Object Net realizes smooth modeling of gene regulatory networks, metabolic pathways, signaling pathways, etc. XML technology is employed to create a personally visualized simulation environment. The picture shows simulation of Fas ligand induced apoptosis signaling pathway.


TEL: 03-5449-5615
FAX: 03-5449-5442

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