Advances in Computing
Answer:
Introduction:
Bayesian Model Selection Framework for Identifying Growth Patterns in Filamentous Fungi
The models for the description of different stages o
f development of fungi were understood in this paper. The authors have helped me to understand the method for quantification of modeling error regarding the various models that exist for predicting the growth pattern for filamentous fungi. I have understood that the errors in the mathematical modeling arise due to uncertain colony architecture and various cellular signals, which depends upon the various environmental factors. Since there exists a gap between the modeling and reality, a unified computational framework based upon Bayesian have been developed and understood for quantification of the modeling errors and ranks were assigned to the models based on performance. Further, it was well understood that the Bayesian model is the mathematical extension of Occam’s razor.
The paper has developed a systematic framework for comparison of the model uncertainties based on Bayesian model. Since the Bayesian model compares the real data and the data from the different models, I can use the difference between the ideal result and the real result to understand the model flaws. Apart from determination of model flaws, the work will also empower the students with the knowledge of models parameters for selection of better models. This comparison of the models will help in the achievement of the tradeoff between the data fitness and the complexity of the model. The comparison will not only help me in calibration of the models but will also help as a guiding tool for further research and refinements. This model will assist the students and researcher to understand the existing models better and will help in the construction of the better complete model in future.
Reference
Gelman, A. and Shalizi, C.R., 2013. Philosophy and the practice of Bayesian statistics. British Journal of Mathematical and Statistical Psychology, 66(1), pp.8-38.
Klipp, E., Liebermeister, W., Wierling, C., Kowald, A. and Herwig, R., 2016.Systems biology: a textbook. John Wiley & Sons.
Lin, X., Terejanu, G., Shrestha, S., Banerjee, S. and Chanda, A., 2016. Bayesian model selection framework for identifying growth patterns in filamentous fungi. Journal of theoretical biology, 398, pp.85-95.
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