Mining manufacturing data for discovery of high productivity process characteristics

Journal of Biotechnology

Volumn 147, Issue 3-4, 2010, Pages 186-197

  Charaniya, Salim ^a   Le, Huong ^a   Rangwala, Huzefa ^b   Mills, Keri ^c   Johnson, Kevin ^c   Karypis, George ^a   Hu, Wei Shou ^a  

^a University of Minnesota   (United States)

^b George Mason University   (United States)

^c GENENTECH INC   (United States)

Author keywords

Bioprocess; Cell culture; Data mining; Manufacturing; Multivariate data analysis; Support vector machine

Indexed keywords

BIOPROCESSES; BIOPRODUCTS; CELL CULTURE PROCESS; COMPLEX CHARACTERISTICS; DATA ARCHIVING; GENENTECH; HIGH PRODUCTIVITY; KERNEL BASED APPROACH; MANUFACTURING FACILITY; MANUFACTURING FLOOR; MANUFACTURING STAGES; MULTIVARIATE DATA ANALYSIS; PERFORMANCE PARAMETERS; PREDICTIVE MODELS; PROCESS CHARACTERISTICS; PROCESS PARAMETERS; PRODUCTION PERFORMANCE; PRODUCTION RUN; REAL-TIME DECISION MAKING; SUPPORT VECTOR REGRESSION (SVR); TIME DYNAMIC;

CELL CULTURE; DATA MINING; DATA WAREHOUSES; DIGITAL STORAGE; MULTIVARIANT ANALYSIS; PROCESS MONITORING; SUPPORT VECTOR MACHINES;

MANUFACTURE;

ANIMAL CELL; ARTICLE; BIOREACTOR; BIOTECHNOLOGY; CELL CULTURE; DATA MINING; DATA PROCESSING; DECISION MAKING; NONHUMAN; PRIORITY JOURNAL; PRODUCTIVITY; ALGORITHM; CLUSTER ANALYSIS; METHODOLOGY;

ALGORITHMS; BIOREACTORS; BIOTECHNOLOGY; CLUSTER ANALYSIS; DATA MINING;

EID: 78349281210     PISSN: 01681656     EISSN: 18734863     Source Type: Journal    
DOI: 10.1016/j.jbiotec.2010.04.005     Document Type: Article

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