Welcome to Our Project Website: Genome Stability, Cancer Genomics & Systems Biology


  • Cancer is a major public health problem with more than a quarter of deaths attributable to cancer. Worldwide, more than 7.5 million people died of cancer and more than 12 million new cases of cancer were diagnosed in 2007. According to the World Health Organisation (WHO), cancer rates could increase to 15 million new cases by 2030, unless progress is made in understanding and controlling cancer, those numbers are expected to rise to 17.5 million deaths and 27 million new cases in 2050.

  • Cancer encompasses more than 100 distinct diseases with diverse risk factors and epidemiology which originate from most of the cell types and organs of the human body and which are characterized by relatively unrestrained proliferation of cells that can invade beyond normal tissue boundaries and metastasize to distant organs.

  • Once thought of cancer as a single disease, it is now understood that cancers consist of a large number of different conditions. In almost all forms, however, cancer changes the genetic blueprint, or genomes, of cells, and causes disruptions within normal biological pathways, leading to uncontrolled cell growth. Because genomic changes are often specific to a particular type or stage of cancer, systematically mapping the changes that occur in each cancer could provide the foundation for research to identify new therapies, diagnostics and preventive strategies.

  • The The Cancer Genome Atlas (TCGA) was lanched in 2006, and aimed to elucidate genetics alteration of 20 cancers, and the International Cancer Genome Consortium (ICGC) was started in late of 2007 to analyze the cancer genome of 50 cancers around the world.

  • We are interested in developing the needed bioinformatics and computatinal systems biology tools and knowledgebases allowing data queries by linking cancer genomic signatures (DNA methylation, gene expression, copy number variation etc.) to relevant clinical information; and also these tools for providing a novel data integration framework that allows simultaneous visualization of different types of data in the context of biological network. We hope these tools will be useful to facilitate hypothesis generation for investigators.

More to come ...



This site is © Copyright by the Distinguished Integrative Bioinformatics Team.
Project Development Site Maintained by Dr. Jeff Chen.