Associate Professor Mik Black
Department of Biochemistry
University of Otago, New Zwealand
In the current research environment, the ability to manage, analyse and interpret data produced by high-throughput sequencing platforms has become an essential skill for both wet- and dry-lab researchers. While a number of options exist for outsourcing these tasks, the reality is that researchers still need (and desire) a level of analytic skill that allows them to perform basic exploratory analysis of their data, without having to rely on external assistance.
In this talk, I will discuss some of the initiatives that have been undertaken in New Zealand and Australia to provide both genomics and bioinformatics support for researchers, as well as highlighting some of the tools and skills that help to ensure the robustness and reproducibility of the analyses being carried out.
Mik received a BSc(Hons) in statistics from the University of Canterbury, and a MSc (mathematical statistics) and PhD (statistics) from Purdue University. After completing his PhD in 2002, Mik returned to New Zealand to work as a lecturer in the Department of Statistics at the University of Auckland. An ongoing involvement in a number of Dunedin-based collaborative genomics projects resulted in a move to the University of Otago in 2006. Mik’s research focuses on the development and application of statistical methods for the analysis of data from genomics experiments, with a particular emphasis on human disease. Mik is also heavily involved in two major initiatives designed to put in place sustainable national research infrastructure for NZ: NZGL (New Zealand Genomics Ltd) for genomics (where he was the interim Bioinformatics Team Leader during 2012-2013), and NeSI (New Zealand eScience Infrastructure) for computing/eResearch.