Related Publications

1. Wu, Z., Pang, W. & Coghill, GM. (2015). 'An integrative top-down and bottom-up qualitative model construction framework for exploration of biochemical systems'. Soft Computing. DOI: 10.1007/s00500-014-1467-6

2. Pang, W. & Coghill, GM. (2015). 'QML-AiNet: an immune network approach to learning qualitative differential equation models'. Applied Soft Computing, vol 27, pp. 148-157. DOI: 10.1016/j.asoc.2014.11.008

3. Pang, W. & Coghill, GM. (2015). 'Qualitative, Semi-quantitative, and Quantitative Simulation of the Osmoregulation System in Yeast'. BioSystems, vol 131, pp. 40-50. DOI: 10.1016/j.biosystems.2015.04.003

4. Wu, Z., Pang, W. & Coghill, GM. (in press). 'An Integrated Qualitative and Quantitative Biochemical Model Learning Framework Using Evolutionary Strategy and Simulated Annealing'. Cognitive Computation. DOI: 10.1007/s12559-015-9328-x

5. Pang, W. & Coghill, GM. (2014). 'QML-Morven: A Novel Framework for Learning Qualitative Differential Equation Models using Both Symbolic and Evolutionary Approaches'. Journal of Computational Science, vol 5, no. 5, pp. 795–808. DOI: 10.1016/j.jocs.2014.06.002

6. Pang, W. & Coghill, GM. (2011). 'An immune-inspired approach to qualitative system identification of biological pathways'. Natural Computing, vol 10, no. 1, pp. 189-207. DOI: 10.1007/s11047-010-9212-2

7. Pang, W. & Coghill, GM. (2014). 'An immune network approach to learning qualitative models of biological pathways'. in 2014 IEEE Congress on Evolutionary Computation (IEEE CEC 2014). IEEE Press, pp. 1030-1037. DOI: 10.1109/CEC.2014.6900393

8. Wu, Z., Pang, W. & Coghill, GM. (2013). 'Stepwise modelling of biochemical pathways based on qualitative model learning'. in Y Jin & SA Thomas (eds), Proceeding of the 13th UK Workshop on Computational Intelligence. Computational Intelligence (UKCI 2013). IEEE Explore, pp. 31-37. DOI: 10.1109/UKCI.2013.6651284

9. Pang, W. & Coghill, GM. (2013). 'An Immune Network Approach to Qualitative System Identification of Biological Pathways'. in M Bhatt, P Struss & C Freksa (eds), 27th International Workshop on Qualitative Reasoning (QR 2013).

10. Pang, W. & Coghill, GM. (2011). 'A fast opt-AINet approach to qualitative model learning with a modified mutation operator'. in Proceedings of the 11th UK Workshop on Computational Intelligence (UKCI).

11. Pang, W. & Coghill, GM. (2010). 'QML-AiNet: An Immune-inspired Network Approach to Qualitative Model Learning'. in E Hart, C McEwan, J Timmis & A Hone (eds), proc. of 8th International Conference on Artificial Immune Systems (ICARIS 2010). Lecture Notes in Computer Science, vol. 6209, Springer-Verlag, Berlin Heidelberg, pp. 223-236. DOI: 10.1007/978-3-642-14547-6_18

12. Pang, W. & Coghill, GM. (2010). 'Learning Qualitative Metabolic Models Using Evolutionary Methods'. in 2010 Fifth International Conference on Frontier of Computer Science and Technology. DOI: 10.1109/FCST.2010.57

13. Pang, W. & Coghill, GM. (2009). 'An Immune-Inspired Approach to Qualitative System Identification of the Detoxification Pathway of Methylglyoxal'. in Lecture Notes in Computer Science. vol. 5666, Lecture Notes in Computer Science, vol. 5666, Springer, pp. 151-164.

DOI: 10.1007/978-3-642-03246-2_17

14. Liu, H., Coghill, G.M. and Barnes, D. (2009) Fuzzy Qualitative Trigonometry, International Journal of Approximate Reasoning, vol. 51(1), pp. 71-88.

15. Pang, W., Coghill, GM. & Bruce, AM. (2012). Non-constructive interval simulation of dynamic systems. Technical Report ABDN–CS–12–02, vol. ABDN–CS–12–02, Department of Computing Science, University of Aberdeen, Aberdeen, AURA: abdntechrep12_02.pdf

16. Pang, W. & Coghill, GM. (2006). 'Evolutionary approaches for learning qualitative compartment metabolic models'. in Proceeding of the 6th annual UK Workshop on Computational Intelligence. Leeds, UK, pp. 11-16

17. Pang, W. & Coghill, GM. (2006). 'EQML- An Evolutionary Qualitative Model Learning Framework'. in 2nd European Symposium on Nature-inspired Smart Information Systems.Puerto de la Cruz, Tenerife, Spain, pp. 1-7.

[ONLINE] AURA: AB14_Coghill_Pang.pdf

18. Mehdi Khoury, Frank Guerin, George Macleod Coghill: Learning dynamic models of compartment systems by combining symbolic regression with fuzzy vector envisionment. GECCO (Companion) 2007: 2769-2776

19. George Macleod Coghill, Honghai Liu, Allan Bruce, Carol Wisley: Fuzzy Qualitative Reasoning about Dynamic Systems Containing Trigonometric Relationships. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 19(3): 477-498 (2011)