About the Project
Complex networks can be used to describe a wide variety of systems of high technological and intellectual importance, such as biomedical or disease-related networks. Data science and network analysis aim to model individual pairwise interactions between genes and their products in a holistic manner, so that the properties of the entire system dynamics, such as self-organisation or adaptiveness, can be revealed.
In the study of biological systems, community structure detection, as aprt of Data and Network Science, provides a topological perspective of cellular interactions at system-level and can lead to critical insights into the functional organisation of the underlying molecular processes. Here, we propose application of complex systems approaches in the study of cancer therapy signalling. We propose a tight interaction between computational and experimental scientists to establishing accurate models of molecular interactions in cancerous cells engendered by monoclonal antibodies to a tumour antigen. In particular, we will investigate mechanisms where antibodies induce downstream signals to destroy cancer cells. We will apply our methodologies to networks constructed from experimental data, including gene expression and phosphorylation data, to represent and compare system behaviour under various conditions.
This work will contribute towards understanding the combination of pathways and other molecular interactions associated with antibody-mediated cancer clearance. Overall, our proposal has a strong interdisciplinary and translational outlook in establishing the use of Data Science in an emerging biomedical system, such as the use of antibody biologicals for cancer therapy.
Application Deadline
Monday 28th May 2018, 11:59
References
1. Josephs DH, Bax HJ, Dodev T, Georgouli M, Nakamura M, Pellizzari G, Saul L, Karagiannis P, Cheung A, Herraiz C, Ilieva KM, Correa I, Fittall M, Crescioli S, Gazinska P, Woodman N, Mele S, Chiaruttini G, Gilbert AE, Koers A, Bracher M, Selkirk C, Lentfer H, Barton C, Lever E, Muirhead G, Tsoka S, Canevari S, Figini M, Montes A, Downes N, Dombrowicz D, Corrigan CJ, Beavil AJ, Nestle FO, Jones PS, Gould HJ, Sanz-Moreno V, Blower PJ, Spicer JF, Karagiannis SN. Anti-Folate Receptor-α IgE but not IgG Recruits Macrophages to Attack Tumors via TNFα/MCP-1 Signaling. Cancer Res. 77(5): 1127-1141, 2017.
2. L. Bennett, A. Kittas, G. Muirhead, L. G. Papageorgiou, S. Tsoka, “Detection of Composite Communities in Multiplex Biological Networks”, Scientific Reports, 5:10345, 2015.
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