Managing uncertainty in metabolic network structure and improving predictions using EnsembleFBA
出版年份 2017 全文链接
标题
Managing uncertainty in metabolic network structure and improving predictions using EnsembleFBA
作者
关键词
Small molecules, Gene prediction, Metabolic networks, Pneumococcus, Pseudomonas aeruginosa, Drug metabolism, Streptococcus, Group D streptococci
出版物
PLoS Computational Biology
Volume 13, Issue 3, Pages e1005413
出版商
Public Library of Science (PLoS)
发表日期
2017-03-07
DOI
10.1371/journal.pcbi.1005413
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Efficacy of species-specific protein antibiotics in a murine model of acute Pseudomonas aeruginosa lung infection
- (2016) Laura C. McCaughey et al. Scientific Reports
- Essential genome ofPseudomonas aeruginosain cystic fibrosis sputum
- (2015) Keith H. Turner et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- fastGapFill: efficient gap filling in metabolic networks
- (2014) Ines Thiele et al. BIOINFORMATICS
- Efficiently gap-filling reaction networks
- (2014) Mario Latendresse BMC BIOINFORMATICS
- Long-term phenotypic evolution of bacteria
- (2014) Germán Plata et al. NATURE
- Likelihood-Based Gene Annotations for Gap Filling and Quality Assessment in Genome-Scale Metabolic Models
- (2014) Matthew N. Benedict et al. PLoS Computational Biology
- Comparative Genome-Scale Reconstruction of Gapless Metabolic Networks for Present and Ancestral Species
- (2014) Esa Pitkänen et al. PLoS Computational Biology
- Comparative Metabolic Systems Analysis of Pathogenic Burkholderia
- (2013) J. A. Bartell et al. JOURNAL OF BACTERIOLOGY
- Basic and applied uses of genome-scale metabolic network reconstructions of Escherichia coli
- (2013) D. McCloskey et al. Molecular Systems Biology
- Reconstruction and Validation of a Genome-Scale Metabolic Model for the Filamentous Fungus Neurospora crassa Using FARM
- (2013) Jonathan M. Dreyfuss et al. PLoS Computational Biology
- The RAVEN Toolbox and Its Use for Generating a Genome-scale Metabolic Model for Penicillium chrysogenum
- (2013) Rasmus Agren et al. PLoS Computational Biology
- Defining the core Arabidopsis thaliana root microbiome
- (2012) Derek S. Lundberg et al. NATURE
- Global probabilistic annotation of metabolic networks enables enzyme discovery
- (2012) Germán Plata et al. Nature Chemical Biology
- OptCom: A Multi-Level Optimization Framework for the Metabolic Modeling and Analysis of Microbial Communities
- (2012) Ali R. Zomorrodi et al. PLoS Computational Biology
- Reconciliation of Genome-Scale Metabolic Reconstructions for Comparative Systems Analysis
- (2011) Matthew A. Oberhardt et al. PLoS Computational Biology
- Metabolic Network Analysis of Pseudomonas aeruginosa during Chronic Cystic Fibrosis Lung Infection
- (2010) M. A. Oberhardt et al. JOURNAL OF BACTERIOLOGY
- High-throughput generation, optimization and analysis of genome-scale metabolic models
- (2010) Christopher S Henry et al. NATURE BIOTECHNOLOGY
- A protocol for generating a high-quality genome-scale metabolic reconstruction
- (2010) Ines Thiele et al. Nature Protocols
- BLAST+: architecture and applications
- (2009) Christiam Camacho et al. BMC BIOINFORMATICS
- Applications of genome-scale metabolic reconstructions
- (2009) Matthew A Oberhardt et al. Molecular Systems Biology
- The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases
- (2009) Ron Caspi et al. NUCLEIC ACIDS RESEARCH
- GrowMatch: An Automated Method for Reconciling In Silico/In Vivo Growth Predictions
- (2009) Vinay Satish Kumar et al. PLoS Computational Biology
- Ensemble Modeling of Metabolic Networks
- (2008) Linh M. Tran et al. BIOPHYSICAL JOURNAL
- Genome-Scale Metabolic Network Analysis of the Opportunistic Pathogen Pseudomonas aeruginosa PAO1
- (2008) M. A. Oberhardt et al. JOURNAL OF BACTERIOLOGY
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started