Common Research Facilities
Contact
Medical Institute of Bioregulation, Kyushu University
3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, JAPAN
TEL +81-92-642-6814
FAX +81-92-642-6246

The 764th MIB Seminar
(Joint Usage/Research Center for the Multi-stratified Host Defense System)

[Seminar in English]

Title

Applications of systems and network approaches to the investigation of human diseases.

Speaker

Dr. Jean-Marc Schwartz
Senior Lecturer
Faculty of Biology, Medicine and Health
University of Manchester, UK

Date

Jan. 22 (Mon), 2018
16:00~17:00

Venue

Seminar Room 105, 1F, Biomedical Research Station
No.1 on the following linked map.
(http://www.kyushu-u.ac.jp/f/30074/Hospital_en-2017.pdf)

Abstract

Network and systems-based approaches are increasingly used to study dysregulated molecular components in diseases. By modelling the relations between genes/proteins in an integrative way, we can gain better understanding of the processes and pathways involved in disorders and infer their causal regulators, paving the way for the development of new treatments. In this seminar, we will describe different approaches enabling us to model disease systems. First, we will present a Boolean modelling technique applied to understand the mechanisms of action of Herceptin, a drug which is widely used to treat breast cancer but whose action is hampered in some cases by the development of resistance in tumour cells. Next, we will present an integration of network analysis with gene expression (RNA-sequencing) data applied to the study of skeletal diseases, and show how this integration helps to discover new pathways and regulators involved in these disorders.

Publications

  1. Hetmanski et al (2016). A MAPK-driven feedback loop suppresses Rac activity to promote RhoA-driven cancer cell invasion. PLoS Computational Biology 12: e1004909.
  2. Dunn et al (2016). Gene expression changes in damaged osteoarthritic cartilage identify a signature of non-chondrogenic and mechanical responses. Osteoarthritis and Cartilage 24: 1431-40.
  3. Schwartz et al (2015). Metabolic flux prediction in cancer cells with altered substrate uptake. Biochem Soc Trans 43: 1177-81.
  4. Soul et al (2015). PhenomeExpress: A refined network analysis of expression datasets by inclusion of known disease phenotypes. Scientific Reports 5: 8117.
  5. Tian et al (2013). Dynamics of DNA damage induced pathways to cancer. PLoS One 8: e72303.

Contact

Division of System Cohort, MIB
Yoshihiro Yamanishi
Tel:092(642)6925