Inductive process modeling of Rab5-Rab7 conversion in endocytosis

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8140 LNAI, Issue , 2013, Pages 265-280

  Tanevski, Jovan ^a   Todorovski, Ljupčo ^b   Kalaidzidis, Yannis ^c   Džeroski, Sašo ^a,d  

^a JO EF STEFAN INSTITUTE   (Slovenia)

^b UNIVERSITY OF LJUBLJANA   (Slovenia)

^c MAX PLANCK INSTITUTE OF MOLECULAR CELL BIOLOGY AND GENETICS   (Germany)

^d Centre of Excellence for Integrated Approaches in Chemistry and Biology of Proteins   (Slovenia)

Author keywords

[No Author keywords available]

Indexed keywords

ANTIGEN-ANTIBODY REACTIONS; DYNAMICAL SYSTEMS; EXPERIMENTS; PROCESS ENGINEERING; PROTEINS;

DOMAIN KNOWLEDGE; EQUATION DISCOVERY; FORMAL REPRESENTATIONS; INDUCTIVE PROCESS; KEY PROCESS; OBSERVED DATA;

MOLECULAR BIOLOGY;

EID: 84888379609     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-40897-7_18     Document Type: Conference Paper

References (10)

1. Bridewell, W., Langley, P., Todorovski, L., Džeroski, S.: Inductive process modelling. Machine Learning 71, 109-130 (2008)
2. del Conte-Zerial, P., Brusch, L., Rink, J., Collinet, C., Kalaidzidis, Y., Zerial, M., Deutsch, A.: Membrane identity and GTPase cascades regulated by toggle and cut-out switches. Molecular Systems Biology 4 (2008)
3. Durillo, J.J., Nebro, A.J.: jmetal: A java framework for multi-objective optimization. Advances in Engineering Software 42, 760-771 (2011)
4. Džeroski, S., Todorovski, L.: Encoding and using domain knowledge on population dynamics for equation discovery. In: Magnani, L., Nersessian, N.J. (eds.) Logical and Computational Aspects of Model-Based Reasoning, pp. 227-247. Kluwer Academic Publishers (2002)
5. Džeroski, S., Todorovski, L.: Discovering dynamics. In: Proc. Tenth International Conference on Machine Learning, pp. 97-103. Morgan Kaufmann (1993)
6. Hastie, T., Tibshirani, R., Friedman, J.H.: The elements of statistical learning: data mining, inference, and prediction. Springer (2001)
7. Hindmarsh, A.C., Brown, P.N., Grant, K.E., Lee, S.L., Serban, R., Shumaker, D.E., Woodward, C.S.: SUNDIALS: Suite of nonlinear and differential/algebraic equation solvers. ACM Trans. Math. Softw. 31(3), 363-396 (2005)
8. Langley, P., Simon, H., Bradshaw, G., Zytkow, J.: Scientific Discovery: Computational Explorations of the Creative Processes. The MIT Press (1987)
9. Tashkova, K., Korošec, P., Šilc, J., Todorovski, L., Džeroski, S.: Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis. BMC Systems Biology 5(1), 159 (2011)
10. Čerepnalkoski, D., Taškova, K., Todorovski, L., Atanasova, N., Džeroski, S.: The influence of parameter fitting methods on model structure selection in automated modeling of aquatic ecosystems. Ecological Modelling 245, 136-165 (2012)