Qualitative Reasoning for Understanding the Behaviour of Complex Biomolecular Networks

Ali Ayadi, Cecilia Zanni-Merk, François de Beuvron de Bertrand

2016

Abstract

Understanding the dynamical behaviour of cellular systems requires the development of effective modelling techniques. The modeling aims to facilitate the study and understanding of the dynamic behaviour of these systems, by the simulation of their designed models. Complex biomolecular networks are the basis of these models. In this paper, we propose a method of qualitative reasoning, based on a formal logical modeling, to qualitatively simulate the biomolecular network and interpret it behaviour over time. The power of our approach is illustrated by applying it to the case study of the autoregulation of the bacteriophage T4 gene 32.

References

  1. Ayadi, A., Zanni-Merk, C., de Bertrand de Beuvron, F., and Krichen, S. (2016). Logical and semantic modeling of complex biomolecular networks. Procedia Computer Science, 96:475 - 484. Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 20th International Conference KES2016.
  2. Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., Fierer, N., Pena, A. G., Goodrich, J. K., Gordon, J. I., et al. (2010). Qiime allows analysis of high-throughput community sequencing data. Nature methods, 7(5):335-336.
  3. De Kleer, J. and Brown, J. S. (1984). A qualitative physics based on confluences. Artificial intelligence, 24(1- 3):7-83.
  4. Fielding, N. and Schreier, M. (2001). Introduction: On the compatibility between qualitative and quantitative research methods. In Forum Qualitative Sozialforschung/Forum: Qualitative Social Research, volume 2.
  5. Forbus, K. D. (1997). Qualitative reasoning.
  6. Hayes, P. J. et al. (1978). The naive physics manifesto. Institut pour les études sémantiques et cognitives/Université de Genève.
  7. Ingalls, B. (2012). Mathematical modelling in systems biology: An introduction.
  8. Karp, G. (2010). Biologie cellulaire et moléculaire: Concepts and experiments. De Boeck Supérieur.
  9. Lewin, B. and Sanlaville, C. (1998). Gènes VI. De Boeck Supérieur.
  10. Travé-Massuyès, L. (1997). Le raisonnement qualitatif pour les sciences de l'ingénieur (coll. diagnostic et maintenance). Hermes Science Publications.
  11. Wu, F., Chen, L., Wang, J., and Alhajj, R. (2014a). Biomolecular networks and human diseases. BioMed research international, 2014.
  12. Wu, F.-X., Wu, L., Wang, J., Liu, J., and Chen, L. (2014b). Transittability of complex networks and its applications to regulatory biomolecular networks. Scientific reports, 4.
Download


Paper Citation


in Harvard Style

Ayadi A., Zanni-Merk C. and de Beuvron de Bertrand F. (2016). Qualitative Reasoning for Understanding the Behaviour of Complex Biomolecular Networks . In Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2016) ISBN 978-989-758-203-5, pages 144-149. DOI: 10.5220/0006065901440149


in Bibtex Style

@conference{keod16,
author={Ali Ayadi and Cecilia Zanni-Merk and François de Beuvron de Bertrand},
title={Qualitative Reasoning for Understanding the Behaviour of Complex Biomolecular Networks},
booktitle={Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2016)},
year={2016},
pages={144-149},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006065901440149},
isbn={978-989-758-203-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2016)
TI - Qualitative Reasoning for Understanding the Behaviour of Complex Biomolecular Networks
SN - 978-989-758-203-5
AU - Ayadi A.
AU - Zanni-Merk C.
AU - de Beuvron de Bertrand F.
PY - 2016
SP - 144
EP - 149
DO - 10.5220/0006065901440149