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. 2020 Aug 21;38(10):1169–1186. doi: 10.1016/j.tibtech.2020.07.004

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Representation of Transcriptomic and Proteomic Data, Phenomenological Model and Data Analytic Methods.

(A) Protein versus RNA intensities for Chinese hamster ovary (CHO) cells; (B) codon frequency for CHO cells. It is important to optimize the codons of human proteins to increase their expression; (C) equations for a phenomena-logical model of microbial production of streptokinase based on the original concepts of specific growth rates, as first proposed by Monod in 1941 [47]; the variables represented in this formulation of ordinary differential equations are based on active (x_a) and total (x_t) microbial biomass, as listed in (D); (E) depiction of error back propagation in a deep learning model developed to estimate important parameters in the fermentation of streptokinase. The semisupervised deep neural network-based soft sensor has a superior overall performance to that of support vector regression specifically for cases with a larger unlabeled dataset. Reproduced, with permission, from [51] (A), [44] (B), and [46] (D,E).

Representation of Transcriptomic and Proteomic Data, Phenomenological Model and Data Analytic Methods.

(A) Protein versus RNA intensities for Chinese hamster ovary (CHO) cells; (B) codon frequency for CHO cells. It is important to optimize the codons of human proteins to increase their expression; (C) equations for a phenomena-logical model of microbial production of streptokinase based on the original concepts of specific growth rates, as first proposed by Monod in 1941 [47]; the variables represented in this formulation of ordinary differential equations are based on active (x_a) and total (x_t) microbial biomass, as listed in (D); (E) depiction of error back propagation in a deep learning model developed to estimate important parameters in the fermentation of streptokinase. The semisupervised deep neural network-based soft sensor has a superior overall performance to that of support vector regression specifically for cases with a larger unlabeled dataset. Reproduced, with permission, from [51] (A), [44] (B), and [46] (D,E).