[go: up one dir, main page]

Burgard et al., 2003 - Google Patents

Optknock: a bilevel programming framework for identifying gene knockout strategies for microbial strain optimization

Burgard et al., 2003

View PDF
Document ID
908952200922180910
Author
Burgard A
Pharkya P
Maranas C
Publication year
Publication venue
Biotechnology and bioengineering

External Links

Snippet

The advent of genome‐scale models of metabolism has laid the foundation for the development of computational procedures for suggesting genetic manipulations that lead to overproduction. In this work, the computational OptKnock framework is introduced for …
Continue reading at www.academia.edu (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/12—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for modelling or simulation in systems biology, e.g. probabilistic or dynamic models, gene-regulatory networks, protein interaction networks or metabolic networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/18—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for functional genomics or proteomics, e.g. genotype-phenotype associations, linkage disequilibrium, population genetics, binding site identification, mutagenesis, genotyping or genome annotation, protein-protein interactions or protein-nucleic acid interactions
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for programme control, e.g. control unit
    • G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/46—Multiprogramming arrangements
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer

Similar Documents

Publication Publication Date Title
Burgard et al. Optknock: a bilevel programming framework for identifying gene knockout strategies for microbial strain optimization
AU2003256480B2 (en) Method for determining gene knockout strategies
US8108152B2 (en) Method for redesign of microbial production systems
Yang et al. EMILiO: a fast algorithm for genome-scale strain design
Fowler et al. Increased malonyl coenzyme A biosynthesis by tuning the Escherichia coli metabolic network and its application to flavanone production
Pharkya et al. Exploring the overproduction of amino acids using the bilevel optimization framework OptKnock
Edwards et al. Robustness analysis of the escherichiacoli metabolic network
Liu et al. A constraint-based model of Scheffersomyces stipitis for improved ethanol production
Matsuoka et al. Current status and future perspectives of kinetic modeling for the cell metabolism with incorporation of the metabolic regulation mechanism
Pereira et al. Reconstruction of a genome-scale metabolic model for Actinobacillus succinogenes 130Z
Bruggeman et al. Trade‐offs between the instantaneous growth rate and long‐term fitness: consequences for microbial physiology and predictive computational models
Lee et al. Genome-scale metabolic network reconstruction and in silico flux analysis of the thermophilic bacterium Thermus thermophilus HB27
Oh et al. Multiobjective flux balancing using the NISE method for metabolic network analysis
Garcia et al. Harnessing natural modularity of metabolism with goal attainment optimization to design a modular chassis cell for production of diverse chemicals
Apaydin et al. Robust mutant strain design by pessimistic optimization
AU2004322970B2 (en) Method for redesign of microbial production systems
Tian et al. Metabolic modeling for design of cell factories
Rizk et al. Redox homeostasis phenotypes in RubisCO‐deficient Rhodobacter sphaeroides via ensemble modeling
DeVilbiss et al. Consistency of cybernetic variables with gene expression profiles: A more rigorous test
Caspeta et al. Systems Metabolic Engineering of Saccharomyces cerevisiae for Production of Biochemicals from Biomass
JP2012104129A (en) Method for redesigning microbiological production system
Tian Computational tools for omics data analysis
Oyetunde Decoding Complexity in Metabolic Networks using Integrated Mechanistic and Machine Learning Approaches
Lee et al. Construction and Applications of Genome‐Scale in silico Metabolic Models for Strain Improvement
Pharkya Optimization based redesign of microbial production systems