Computational Systems Biology

Research Staff

  • Prof. Shigehiko Kanaya

    Shigehiko Kanaya

  • Affiliate Prof. Tadao Sugiura

    Affiliate Prof.
    Tadao Sugiura

  • Assoc.Prof. Altaf-Ul-Amin


  • Affiliate Assoc.Prof.Tetsuo Sato

    Affiliate Assoc.Prof.
    Tetsuo Sato

  • Assist.Prof. Naoaki Ono

    Naoaki Ono

  • Assist.Prof. Mei Kou

    Ming Huang

E-mail skanaya [at], { sugiura, amin-m, tsato, nono, alex-mhuang }[at]

Research Area

1. Systems biology

Biology has been significantly advanced by reductive approaches. Huge biological data sets, such as more than 1,000 genome sequences, have caused a paradigm shift into a holistic approach to understanding living things as systems. We study these approaches by modeling several biological systems to elucidate cellular mechanisms.

2. Network analysis

With the development of omics technologies, it has become imperative to systematically analyze all biological components (genes, mRNA, proteins and metabolites). To meet this challenge, we have developed a clustering algorithm (DPClus) to extract highly connected clusters.

3. Transcriptomes

A transcriptome is defined as a total set of transcripts in an organism. To elucidate transcriptome networks, we study transcriptome analyses using microarrays and new generation sequencers with the use of BL-SOM and novel methods.

4. Metabolomes

Cells consist of a few thousand molecules. Of those, metabolites are mainly produced by enzymatic reactions. The objective of metabolome analysis is to comprehensively identify which particular metabolites affect cellular networks. As a metabolome analysis platform, we have developed a species-metabolite database, KNApSAcK, covering almost all reported metabolites. To date, 50,048 metabolites and 101,500 species-metabolite relationships have been accumulated.

5. Bioimaging and informatics

Bioimaging has become an essential tool for understanding biological phenomena at the micrometer scale and also for medical diagnostics. Due to significant progress in microscope and detection technologies in the last decade, advanced observation methods have been realized, such as three-dimensional observation at the micron scale and super-resolution microscopes with resolution of several 10nm. We develop various microscope and analysis systems based on such emerging technologies.

Three-dimensional and super-resolution microscopes

A micro-nano manipulation system with optical tweezers

fN force measurement and cell palpation systems

6. Medical imaging

A cardiac MRI in clinical imaging for coronary arteries and decision support technology for motion compensation has been developed. Diffusion Tensor MRI (DT-MRI) and tractography techniques are being investigated for the analysis of human brain cognitive functions.


Medical image analysis

7. Volume visualization in biology

We have developed a high speed volume rendering method for visualizing high resolution microscopic 3D images such as two-photon microscopy techniques.

Volume graphics

Neuron tracing

Microscope image analysis

8. Medical engineering and informatics

In collaboration with medical hospitals and other institutions, we develop various medical engineering technologies based on information technology.

Electromyogram and motion analysis

Rehabilitation engineering

Hospital information systems

Key Features

We work in an interdisciplinary field between information technology and bio-medical science. Our aim is to further both bio-medical science and information technology. Students study a wide variety of technologies, such as signal and image processing, imaging technology, optics, and nanotechnologies. We have developed techniques to identify gene function and disease mechanisms at high resolution.

Our laboratory members, who have come from a wide variety of backgrounds, aim to elucidate the robustness and diversity of biological systems throughby chemo- and bio-informatics. In our lab, students study a wide range of areas and attain broad perspectives. We always discuss important issues regarding research to enhance each other's knowledge.

Fig.1 Feature Map: Expression Profile in Bacillus subtilis

Fig.1 Feature map: expression profile in Bacillus subtilis

Fig.2 Main page of "KNApSAcK Family"

Fig.2 Main page of "KNApSAcK Family"

( KNApSAcK_Family/)

Fig.3  Examples of biomedical imaging taken by various imaging schemes

Fig.3 Examples of biomedical imaging taken by various imaging schemes