scholarly article | Q13442814 |
P8978 | DBLP publication ID | journals/biosystems/VilacaRR11 |
P356 | DOI | 10.1016/J.BIOSYSTEMS.2010.11.012 |
P953 | full work available at URL | https://api.elsevier.com/content/article/PII:S0303264710002145?httpAccept=text/plain |
https://api.elsevier.com/content/article/PII:S0303264710002145?httpAccept=text/xml | ||
https://repositorium.sdum.uminho.pt/bitstream/1822/14326/1/BioSystems-regulPlugin-pubVersion.pdf | ||
P698 | PubMed publication ID | 21144882 |
P5875 | ResearchGate publication ID | 49670848 |
P50 | author | Isabel Rocha | Q47449076 |
Miguel Rocha | Q56871204 | ||
P2093 | author name string | Paulo Vilaça | |
P2860 | cites work | An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR) | Q21194867 |
Structural and functional analysis of cellular networks with CellNetAnalyzer | Q21202799 | ||
Evolutionary programming as a platform for in silico metabolic engineering | Q25257616 | ||
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Optknock: a bilevel programming framework for identifying gene knockout strategies for microbial strain optimization | Q29616020 | ||
Integrating high-throughput and computational data elucidates bacterial networks | Q30928624 | ||
Predicting essential components of signal transduction networks: a dynamic model of guard cell abscisic acid signaling | Q33257261 | ||
The regulatory network of E. coli metabolism as a Boolean dynamical system exhibits both homeostasis and flexibility of response | Q33321940 | ||
Natural computation meta-heuristics for the in silico optimization of microbial strains | Q33387681 | ||
Logical modelling of regulatory networks with GINsim 2.3. | Q33442155 | ||
AIBench: a rapid application development framework for translational research in biomedicine | Q33521794 | ||
OptORF: Optimal metabolic and regulatory perturbations for metabolic engineering of microbial strains | Q33567324 | ||
Advances in flux balance analysis | Q33973453 | ||
Regulation of Gene Expression in Flux Balance Models of Metabolism | Q34101809 | ||
Genetic networks with canalyzing Boolean rules are always stable | Q37693857 | ||
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P433 | issue | 3 | |
P407 | language of work or name | English | Q1860 |
P921 | main subject | metabolism | Q1057 |
regulation of gene expression | Q411391 | ||
modelling biological systems | Q4299308 | ||
P304 | page(s) | 435-441 | |
P577 | publication date | 2010-12-07 | |
P1433 | published in | BioSystems | Q2025895 |
P1476 | title | A computational tool for the simulation and optimization of microbial strains accounting integrated metabolic/regulatory information | |
P478 | volume | 103 |
Q39412598 | BeReTa: a systematic method for identifying target transcriptional regulators to enhance microbial production of chemicals |
Q39240999 | Gene knockout identification using an extension of Bees Hill Flux Balance Analysis |
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Q38859481 | Genome-scale metabolic models as platforms for strain design and biological discovery |
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Q50923419 | In silico deletion of PtsG gene in Escherichia coli genome-scale model predicts increased succinate production from glycerol. |
Q57788170 | In silico model-guided identification of transcriptional regulator targets for efficient strain design |
Q50918693 | Model-aided atpE gene knockout strategy in Escherichia coli for enhanced succinic acid production from glycerol. |
Q64117653 | OptRAM: In-silico strain design via integrative regulatory-metabolic network modeling |
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