Visualization of complex biological systems: An immune response model using OpenGL

In this paper we present an update on our novel visualization technologies based on cellular immune interaction from both large-scale spatial and temporal perspectives. We do so with a primary motive: to present a visually and behaviourally realistic environment to the community of experimental biologists and physicians such that their knowledge and expertise may be more readily integrated into the model creation and calibration process. Visualization aids understanding as we rely on visual perception to make crucial decisions. For example, with our initial model, we can visualize the dynamics of an idealized lymphatic compartment, with antigen presenting cells (APC) and cytotoxic T lymphocyte (CTL) cells. The visualization technology presented here offers the researcher the ability to start, pause, zoom-in, zoom-out and navigate in 3-dimensions through an idealised lymphatic compartment.

The Queensland Cancer Physics Collaborative and the Quantitative Biomedical Imaging & Characterisation (Q-BIC) Research Group

a presentation about immersive visualised simulation systems, image analysis and GPGPU Techonology

Practical introduction to development of sage applications

Throughout this workshop session we have looked at various configurations of Sage as well as using the Sage UI to run Sage applications (e.g. the image viewer). More advanced usage of Sage has been demonstrated using a Sage compatible version of Paraview highlighting the potential of parallel rendering. The aim of this tutorial session is to give a practical introduction to developing visual content for a tiled display using the Sage libraries. After completing this tutorial you should have the basic tools required to develop your own custom Sage applications. This tutorial is designed for software developers and intermediate programming knowledge is assumed, along with some introductory OpenGL . You will be required to write small portions of C/C++ code to complete this worksheet. However if you do not feel comfortable writing code (or have never written in C or C++), we will be on hand throughout this session so feel free to ask for some help. We have a number of machines in this lab running a VNC client to a virtual machine running Fedora 12. You should all be able to log in with the username “escience”, and password “escience10”. Some of the commands in this worksheet require you to run them as the root user, so note the password as you may need to use it a few times. If you need to access the Internet, then use the username “qpsf01”, password “escience10”

Mathematical modelling of tumour-induced angiogenesis

The growth of solid tumours beyond a critical size is dependent upon angiogenesis, the formation of new blood vessels from an existing vasculature. Tumours may remain dormant at microscopic sizes for some years before switching to a mode in which growth of a supportive vasculature is initiated. The new blood vessels supply nutrients, oxygen, and access to routes by which tumour cells may travel to other sites within the host (metastasize). In recent decades an abundance of biological research has focused on tumour-induced angiogenesis in the hope that treatments targeted at the vasculature may result in a stabilisation or regression of the disease: a tantalizing prospect. The complex and fascinating process of angiogenesis has also attracted the interest of researchers in the field of mathematical biology, a discipline that is, for mathematics, relatively new. The challenge in mathematical biology is to produce a model that captures the essential elements and critical dependencies of a biological system. Such a model may ultimately be used as a predictive tool. In this thesis we examine a number of aspects of tumour-induced angiogenesis, focusing on growth of the neovasculature external to the tumour. Firstly we present a one-dimensional continuum model of tumour-induced angiogenesis in which elements of the immune system or other tumour-cytotoxins are delivered via the newly formed vessels. This model, based on observations from experiments by Judah Folkman et al., is able to show regression of the tumour for some parameter regimes. The modelling highlights a number of interesting aspects of the process that may be characterised further in the laboratory. The next model we present examines the initiation positions of blood vessel sprouts on an existing vessel, in a two-dimensional domain. This model hypothesises that a simple feedback inhibition mechanism may be used to describe the spacing of these sprouts with the inhibitor being produced by breakdown of the existing vessel's basement membrane. Finally, we have developed a stochastic model of blood vessel growth and anastomosis in three dimensions. The model has been implemented in C++, includes an openGL interface, and uses a novel algorithm for calculating proximity of the line segments representing a growing vessel. This choice of programming language and graphics interface allows for near-simultaneous calculation and visualisation of blood vessel networks using a contemporary personal computer. In addition the visualised results may be transformed interactively, and drop-down menus facilitate changes in the parameter values. Visualisation of results is of vital importance in the communication of mathematical information to a wide audience, and we aim to incorporate this philosophy in the thesis. As biological research further uncovers the intriguing processes involved in tumourinduced angiogenesis, we conclude with a comment from mathematical biologist Jim Murray, Mathematical biology is : : : the most exciting modern application of mathematics.