Dr Benjamin Hall
Royal Society University Research Fellow
Modelling the Decision Making Processes of Cancer
There are ~37 000 000 000 000 cells in the adult human body, yet only 1 in 2 adults develop cancers in their lifetime. When you consider the number of opportunities cells in the body have to develop into cancer, the chances of any single cell becoming a cancer are incredibly small. My research uses the same advanced computational techniques which are used to find software bugs in order to understand how the series of errors can occur that eventually lead to cancer development.
To find bugs which rarely occur, computer scientists convert complex software into a simplified form. These computational representations can then be tested to ask broad questions such as- "does this behavior ever happen?" or "do all calculations end with the same result?". I use the same techniques and concepts to address problems in cancer biology. By using a simplified representation of cell communication and decision making processes, I can show how mutations change the cell, and show why some orders are dangerous whilst others are not.
This work could lead to unique insights into cancer evolution, and by testing new ideas with simulation, may enrich the experimental programmes of collaborators. It can also identify new problems in computer science, thereby driving the discovery of algorithms required to solve them. My group also maintains a long standing interest in model systems, specifically C. elegans development and bacterial signalling, and has recently been thinking about the broad issue of reproducibility in computational sciences.
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Emergent Stem Cell Homeostasis in the C. elegans Germline Is Revealed by Hybrid Modeling.Hall BA, Piterman N, Hajnal A, Fisher J. Biophys J. 2015 Jul 21;109(2):428-38. doi: 10.1016/j.bpj.2015.06.007.
Probing the Solution Structure of IKKy and its Interaction with Kaposi’s Sarcoma Associated Herpes Virus Flice Interacting Protein and IKK Subunit Beta by EPR Spectroscopy. Bagnéris C, Rogala KB, Baratchian M, Zamfir V, Kunze MB, Dagles S, Pirker KF, Collins MK, Hall BA, Barrett TE, Kay CW. J Biol Chem. 2015 May 14. pii: jbc.M114.622928. [Epub ahead of print]
Drug target optimization in chronic myeloid leukemia using innovative computational platform. Chuang R, Hall BA, Benque D, Cook B, Ishtiaq S, Piterman N, Taylor A, Vardi M, Koschmieder S, Gottgens B, Fisher J. Sci Rep. 2015 Feb 3;5:8190. doi: 10.1038/srep08190.
Logic programming to predict cell fate patterns and retrodict genotypes in organogenesis. Hall BA, Jackson E, Hajnal A, Fisher J. J R Soc Interface. 2014 Sep 6;11(98):20140245. doi: 10.1098/rsif.2014.0245.
Computing Clinically Relevant Binding Free Energies of HIV-1 Protease Inhibitors.Wright DW, Hall BA, Kenway OA, Jha S, Coveney PV. J Chem Theory Comput. 2014 Mar 11;10(3):1228-1241.
Primary and secondary dimer interfaces of the fibroblast growth factor receptor 3 transmembrane domain: characterization via multiscale molecular dynamics simulations. Reddy T, Manrique S, Buyan A, Hall BA, Chetwynd A, Sansom MS.Biochemistry. 2014 Jan 21;53(2):323-32. doi: 10.1021/bi401576k.
Role of the C-terminal domain in the structure and function of tetrameric sodium channels. Bagnéris C, Decaen PG, Hall BA, Naylor CE, Clapham DE, Kay CW, Wallace BA. Nat Commun. 2013;4:2465. doi: 10.1038/ncomms3465.
Drug Target Optimization in Chronic Myeloid Leukemia Using Innovative Computational Platform. Ryan Chuang1*, Benjamin A. Hall2,3*, David Benque2, Byron Cook2,4, Samin Ishtiaq2, Nir Piterman5, Alex Taylor2, Moshe Vardi6, Steffen Koschmieder7, Berthold Gottgens8,9 & Jasmin Fisher2,10