Process Algebra with Layers: Multi-scale Integration Modelling applied to Cancer Therapy

Citation

Scott E, Nicol J, Coulter J, Hoyle A & Shankland C (2017) Process Algebra with Layers: Multi-scale Integration Modelling applied to Cancer Therapy. In: Bracciali A, Caravagna G, Gilbert D & Tagliaferri R (eds.) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2016. Lecture Notes in Computer Science, 10477. CIBB2016: 13th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistics, Stirling, UK, 01.09.2016-03.09.2016. Cham, Switzerland: Springer, pp. 118-133. https://doi.org/10.1007/978-3-319-67834-4_10

Abstract
We present a novel Process Algebra designed for multi-scale integration modelling: Process Algebra with Layers (PAL). The unique feature of PAL is the modularisation of scale into integrated layers: Object and Population. An Object can represent a molecule, organelle, cell, tissue, organ or any organism. Populations hold specific types of Object, for example, life stages, cell phases and infectious states. The syntax and semantics of this novel language are presented. A PAL model of the multi-scale system of cell growth and damage from cancer treatment is given. This model allows the analysis of different scales of the system. The Object and Population levels give insight into the length of a cell cycle and cell population growth respectively. The PAL model results are compared to wet laboratory survival fractions of cells given different doses of radiation treatment [1]. This comparison shows how PAL can be used to aid in investigations of cancer treatment in systems biology.

Keywords
Systems Biology; Formal Methods; Mathematical Modelling; Cell Cycle; DNA Damage

People

Dr Andrew Hoyle

Senior Lecturer, Mathematics