ABSTRACT: Kidneys of equal size can vary 10-fold in the number of nephrons at birth. Discovering what regulates such variation has been hampered by a lack of quantitative analysis to define kidney development, and factors leading to the formation of the ureteric tree and nephrons are still poorly understood. In recent work, my computational group in collaboration with the developmental biology groups of Melissa Little (MCRI) and Ian Smyth (Monash) created a high-throughput large-scale pipeline for the multi-dimensional analysis and modelling of kidney imaging. Taking advantage of advances in microscopy such as Optical Projection Tomography and high resolution 3D confocal imaging enabled our collaborators to image large numbers of mouse kidneys at high resolution across multiple time points. This has created a massively dense dataset that visualises the multiple stages of kidney development. For example, in one data set we have some 32 ureteric trees imaged in 3D of normal mouse kidneys at 6 distinct stages of development from which some 90,000 measurements have been extracted. In this talk I will outline the mathematical models we created towards making sense these key structures of the kidney and how they develop. The aim is to be able to answer questions such as: is the ureteric branch formation stereotypic or is there a “random” element?; if there is a pattern, what is the nature of the pattern and what drives its formation?; and does patterning vary in mutants? In this presentation our analysis pipeline and algorithms will be described as well as recent results we have obtained in towards answering these questions in kidney patterning. If there is time, some of the other bio-imaging projects within our lab on mathematical modelling, quantification, analysis, automated classification, integration and visualisation of the rich and exciting new data becoming available through fluorescent microscopy imaging and associated technologies will also be briefly covered.

BIO: Dr Nick Hamilton is the Institute Bio-Mathematician at the Institute for Molecular Bioscience (IMB), The University of Queensland, and holds a co-appointment with the Research Computing Centre at UQ. He gained a PhD in Pure Mathematics from the University of Western Australia in 1996 and was subsequently awarded Fellowships in Australia and Belgium. In 2002, Nick made the decision to change fields into the exciting new areas of computational biology and bioinformatics, returned to Australia, and subsequently took up a position within the ARC Centre of Excellence in Bioinformatics at UQ. In 2008 he was appointed as a Laboratory Head at IMB, and Institute Bio-Mathematician in 2014, where he continues to lead a group in bio-image informatics, mathematical modelling and data visualisation, developing methodologies to deal with the current deluge of data that new microscopy imaging technologies have enabled.

About Applied and computational maths seminars

Our seminars bring together UQ's applied and computational mathematics communities.

UQ and invited scientists deliver the presentations, which are informal and promote discussion.

We welcome suggestions for speakers and topics from staff, students and visitors, and encourage students to share their work.

Our seminars are usually held on Thursdays from 3pm to 4pm.

To suggest a topic or speaker, and for more information, contact Dr Dietmar Oelz or Dr Cecilia Gonzalez Tokman.