BioModelAnalyzer: Using formal verification to understand cancer development

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Abstract

Complex networks of genes control cell behaviour. Mutations in these genes can alter the cells healthy processes, causing diseases such as cancer. The pathways in human cells are however poorly characterised, making them unsuitable for many common systems biology methods. Executable modelling approaches use a high level of abstraction to describe genes and their interactions using formal logic, enabling the development of models that can give powerful insights into the controls of cellular behaviour. They have the further advantage that they are amenable to formal verification techniques- mathematical proof-based analyses that can be used to give guarantees of model behaviour, such as proving the robustness of a system at homeostasis or identifying rare failures that may lead to oncogenesis.

BioModelAnalyzer is a web-based tool that allows life scientists to take advantage of this powerful class of techniques in an appropriate user interface. Large complex models can be built and analysed through a graphical user interface. In this talk I will discuss the tool, its ongoing development, and future plans to allow for the analysis of genome-scale models.

About the speaker

Ben Hall is a Royal Society University Research Fellow and Principal Research Fellow at the Department of Medical Physics and Biomedical Engineering, UCL. His laboratory research is focused on using computational approaches to understand how cancer is initiated in aging tissues to aid early detection and propose new therapeutic approaches.

He originally trained in Biochemistry at the University of Oxford, and pursued a DPhil in methods in molecular modelling at Oxford in 2004. He was awarded an Apple Laureate in 2008 for work on cystic fibrosis, and went on to complete postdoctoral positions at Oxford and UCL studying bacterial signalling and HIV drug resistance. He moved to Microsoft Research in 2012 where he switched fields to formal methods in systems biology, before spending 6 years leading a group at the MRC Cancer Unit in Cambridge.

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