Cancer data analysis with new generation sequencing technologies
Project Leader: Saman Halgamuge
Student: Kaushalya Amarasinghe
Collaborators: Jason Li (Peter McCullum Institute for Cancer Research), Rudolf Kruse (Unversity of Magdeburg)
Sponsors: Australian Research Council
Primary Contact: Saman Halgamuge (email@example.com)
Keywords: bioinformatics; cancer; genomics; knowledge discovery
Disciplines: Biomedical Engineering
Domains: Convergence of engineering and IT with the life sciences
Cancer genomics is the study of the cancer genome to identify variations that are unique to cancer. This helps to identify new types of cancer, enhance the knowledge about existing cancers and develop new drugs and personalised treatments for patients. Next Generation Sequencing (NGS) is a technology which is currently used worldwide to generate vast amounts of data. However, development of new methods is required to extract meaningful information from NGS data in order to facilitate cancer genomics. In this research we employ pattern recognition methods to analyse data generated by NGS of the human exome, including individuals with or without cancer. In the first stage, we try to detect copy number variations, one of the main types of aberration in cancer, in whole exome sequencing data.
Recent Research Paper:
Jason Li, Richard Lupat, Kaushalya C Amarasinghe, Ella R Thompson, Maria A Doyle, Georgina L Ryland, Richard W Tothill, Saman K Halgamuge, Ian G Campbell, Kylie L Gorringe, "CONTRA: copy number analysis for targeted resequencing", Bioinformatics, 28 (10), 1307-1313, 2012.