Dr Rachel Wang will be speaking under the theme of translational genomics at BioInfoSummer 2015. We chatted to her about her interests, her work and her reason for choosing a career in Bioinformatics.
What do you think are the most interesting “big questions” in your field?
Network modelling has been an intense area of research interest in a number of fields including statistics, probability, and computer science. Important questions include reconstruction of network edges from covariates, statistical inference of network models, incorporating node features for improved inference, network denoising, and the list goes on.
Please tell us about your research interests and what you are currently working on.
I am interested in inferring various biological networks using genomic data and applying random graph models to the constructed networks. I am also working on statistical inference problems for stochastic block model and its variants.
Do you have favourite applications of your work and what is the impact of these applications?
The study of biology has seen a fast-expanding effort to analyse individual biological components in the context of large-scale, complex networks with interacting constituents. Successful applications can help elucidate the nature of complex biological processes and disease mechanisms in a variety of organisms. Some examples include mapping out gene-gene interactions, annotating regulatory elements on the human genome, and studying the 3D folding of DNA.
Why did you choose to study statistics?
Statistics offers a perfect blend of theory and application. The maths can go as deep as you like; there are also numerous real world applications in which theoretical work can have an immediate and far-reaching impact.