Literature mining supports a next-generation modeling approach to predict cellular byproduct secretion

Metabolic Engineering

Volumn 39, Issue , 2017, Pages 220-227

  King, Zachary A ^a   O'Brien, Edward J ^a   Feist, Adam M ^a,c   Palsson, Bernhard O ^a,b,c  

^a UNIVERSITY OF CALIFORNIA SAN DIEGO   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c Chalmers University of Technology   (Denmark)

Author keywords

Constraint based modeling; Escherichia coli; Genome scale model; Literature mining; ME model

Indexed keywords

BYPRODUCTS; ESCHERICHIA COLI; FORECASTING; GENE EXPRESSION; GENES; METABOLISM;

COMPUTATIONAL MODEL; CONSTRAINT-BASED MODELING; GENOME-SCALE MODEL; LITERATURE MINING; METABOLIC BYPRODUCTS; METABOLIC NETWORK; MODEL PREDICTION; PREDICTIVE POWER;

PHYSIOLOGY;

ISOENZYME; BIOPOLYMER; ESCHERICHIA COLI PROTEIN;

ARTICLE; CELL DEATH; DATA BASE; DATA MINING; ESCHERICHIA COLI; GENE EXPRESSION; GENOME; GENOTYPE PHENOTYPE CORRELATION; METABOLISM; NEXT GENERATION SEQUENCING; NONHUMAN; PREDICTIVE VALUE; PRIORITY JOURNAL; SIMULATION; BIOLOGICAL MODEL; COMPUTER SIMULATION; EVALUATION STUDY; GENE EXPRESSION REGULATION; METABOLIC FLUX ANALYSIS; PHYSIOLOGY; PROCEDURES; PUBLICATION; SECRETION (PROCESS);

BIOPOLYMERS; COMPUTER SIMULATION; DATA MINING; ESCHERICHIA COLI; ESCHERICHIA COLI PROTEINS; GENE EXPRESSION REGULATION, BACTERIAL; METABOLIC FLUX ANALYSIS; MODELS, BIOLOGICAL; PERIODICALS AS TOPIC;

EID: 85007574032     PISSN: 10967176     EISSN: 10967184     Source Type: Journal    
DOI: 10.1016/j.ymben.2016.12.004     Document Type: Article

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