PMID- 17159235
OWN - NLM
STAT- MEDLINE
DCOM- 20061228
LR  - 20190911
IS  - 0273-2289 (Print)
IS  - 0273-2289 (Linking)
VI  - 135
IP  - 2
DP  - 2006 Nov
TI  - Statistical experimental design for bioprocess modeling and optimization 
      analysis: repeated-measures method for dynamic biotechnology process.
PG  - 101-16
AB  - The statistical design of experiments (DOE) is a collection of predetermined 
      settings of the process variables of interest, which provides an efficient 
      procedure for planning experiments. Experiments on biological processes typically 
      produce long sequences of successive observations on each experimental unit 
      (plant, animal, bioreactor, fermenter, or flask) in response to several 
      treatments (combination of factors). Cell culture and other biotech-related 
      experiments used to be performed by repeated-measures method of experimental 
      design coupled with different levels of several process factors to investigate 
      dynamic biological process. Data collected from this design can be analyzed by 
      several kinds of general linear model (GLM) statistical methods such as 
      multivariate analysis of variance (MANOVA), univariate ANOVA (time split-plot 
      analysis with randomization restriction), and analysis of orthogonal polynomial 
      contrasts of repeated factor (linear coefficient analysis). Last, regression 
      model was introduced to describe responses over time to the different treatments 
      along with model residual analysis. Statistical analysis of biprocess with 
      repeated measurements can help investigate environmental factors and effects 
      affecting physiological and bioprocesses in analyzing and optimizing 
      biotechnology production.
FAU - Lee, Kwang-Min
AU  - Lee KM
AD  - Arkansas State University, Environmental Sciences Program, State University, AR 
      72467. klee0922@yahoo.co.kr
FAU - Gilmore, David F
AU  - Gilmore DF
LA  - eng
PT  - Journal Article
PL  - United States
TA  - Appl Biochem Biotechnol
JT  - Applied biochemistry and biotechnology
JID - 8208561
RN  - 0 (Lipids)
SB  - IM
MH  - Analysis of Variance
MH  - Bioreactors
MH  - Biotechnology/*methods
MH  - Fermentation
MH  - Lipids/biosynthesis
MH  - Models, Biological
MH  - Multivariate Analysis
MH  - Research Design
EDAT- 2006/12/13 09:00
MHDA- 2006/12/29 09:00
CRDT- 2006/12/13 09:00
PHST- 2005/08/02 00:00 [received]
PHST- 1999/11/30 00:00 [revised]
PHST- 2006/02/10 00:00 [accepted]
PHST- 2006/12/13 09:00 [pubmed]
PHST- 2006/12/29 09:00 [medline]
PHST- 2006/12/13 09:00 [entrez]
AID - ABAB:135:2:101 [pii]
AID - 10.1385/abab:135:2:101 [doi]
PST - ppublish
SO  - Appl Biochem Biotechnol. 2006 Nov;135(2):101-16. doi: 10.1385/abab:135:2:101.