Barth, G., Beckerich, J.M., Dominguez, A., Kerscher, S., Ogrydziak, D., Titorenko, V. and Gaillardin, C. (2003) Functional genetics of Yarrowia lipolytica In (de Winde, J.H., Ed.), Functional Genetics of Industrial Yeasts, Springer, Berlin, Heidelberg, New York, 227-271. - References

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Barth, G., Beckerich, J.M., Dominguez, A., Kerscher, S., Ogrydziak, D., Titorenko, V. and Gaillardin, C. (2003) Functional genetics of Yarrowia lipolytica In: (de Winde, J.H., Ed.), Functional Genetics of Industrial Yeasts, Springer, Berlin, Heidelberg, New York, 227-271.

has been cited by the following article:

TITLE: Growth rate data fitting of Yarrowia lipolytica NCIM 3589 using logistic equation and artificial neural networks

AUTHORS: Sarat Babu Imandi, Sita Kumari Karanam, Surekha Darsipudi, Hanumantha Rao Garapati

KEYWORDS: Yarrowia lipolytica; Logistic Equation; Artificial Neural Networks

JOURNAL NAME: Advances in Bioscience and Biotechnology, Vol.1 No.1, April 22, 2010

ABSTRACT: Growth rate of Yarrowia lipolytica NCIM 3589 was observed in a fermentation medium consisting of peptone, yeast extract, sodium chloride. Logistic equation was fitted to the growth data (time vs. biomass concentration) and compared with the prediction given by Artificial Neural Networks (ANN). ANN was found to be superior in describing growth characteristics. A single MATLAB programme is developed to fit the growth data by logistic equation and ANN.