11 September 2012
4 - 5pm
Venue: Ground Floor Seminar Room (G010), UniServices House, 70 Symonds Street, Auckland
A Bioengineering PhD Exit Seminar by Yikan Wang, Auckland Bioengineering Institute
Microarray-based gene expression profiling, and more recently RNA-Seq, have been widely used in cancer research and have provided valuable insights into the molecular mechanisms underlying cancer. We proposed data-driven computational models to interpret tumour gene expression information in the context of regulatory network inference, identification of modulators of regulation and tumour classification.
We have: (i) extended a network inference algorithm to reconstruct gene regulatory interactions from the integration of dynamic and steady-state gene expression data; (ii) incorporated combinatorial regulatory interactions into network models for identifying modulators of interactions between transcription factors and their downstream targets; and (iii) provided a bi-clustered molecular-based tumour classification approach to improve prediction of clinical outcome for individual patients.
Gene expression data analyses using these methods have provided additional insights into gene regulatory pathways, regulation of transcriptional activities, and refined tumour subtypes in cancer research. An exciting future challenge will be to improve these models for analysing more advanced high-throughput data, such as RNA-Seq data, proteomic data and DNA methylation data, and to apply them in clinical practice.