Comparison of the estimation capabilities of response surface methodology and artificial neural network for the optimization of recombinant lipase production by E. coli BL21

Journal of Industrial Microbiology and Biotechnology

Volumn 39, Issue 2, 2012, Pages 243-254

  Nelofer, Rubina ^a   Ramanan, Ramakrishnan Nagasundara ^b   Rahman, Raja Noor Zaliha Raja Abd ^a   Basri, Mahiran ^a   Ariff, Arbakariya B ^a  

^a UNIVERSITY PUTRA MALAYSIA   (Malaysia)

^b MONASH UNIVERSITY MALAYSIA   (Malaysia)

Author keywords

Artificial neural network; Lipase production; Process optimization; Recombinant Escherichia coli; Response surface methodology

Indexed keywords

GLUCOSE; RECOMBINANT ENZYME; SODIUM CHLORIDE; TRIACYLGLYCEROL LIPASE;

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; CONTROLLED STUDY; CORRELATION COEFFICIENT; DEPENDENT VARIABLE; ENZYME ACTIVITY; ENZYME INDUCTION; ENZYME SYNTHESIS; ESCHERICHIA COLI; MEASUREMENT ERROR; MODEL; NONHUMAN; PREDICTION; PROCESS OPTIMIZATION; RESPONSE SURFACE METHOD; TEMPERATURE;

ANIMALS; BIOTECHNOLOGY; ESCHERICHIA COLI; GLUCOSE; LIPASE; NEURAL NETWORKS (COMPUTER); SODIUM CHLORIDE; TEMPERATURE;

ESCHERICHIA COLI;

EID: 84857635084     PISSN: 13675435     EISSN: 14765535     Source Type: Journal    
DOI: 10.1007/s10295-011-1019-3     Document Type: Article

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