Markus W Covert
Affiliation: Stanford University
- Integrating metabolic, transcriptional regulatory and signal transduction models in Escherichia coliMarkus W Covert
Department of Bioengineering, Stanford University, 318 Campus Drive, Stanford, CA 94305 5444, USA
Bioinformatics 24:2044-50. 2008..Of current interest is the integration of these approaches with detailed models based on ordinary differential equations (ODEs)...
- Single-cell NF-kappaB dynamics reveal digital activation and analogue information processingSavaş Tay
Department of Bioengineering, Stanford University, Stanford, California 94305, USA
Nature 466:267-71. 2010..These results highlight the value of high-throughput quantitative measurements with single-cell resolution in understanding how biological systems operate...
- Reconstruction of microbial transcriptional regulatory networksMarkus J Herrgard
Department of Bioengineering, Bioinformatics Graduate Program, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093 0412, USA
Curr Opin Biotechnol 15:70-7. 2004..These models can further be combined with genome-scale metabolic models to build integrated models of cellular function including both metabolism and its regulation...
- A forward-genetic screen and dynamic analysis of lambda phage host-dependencies reveals an extensive interaction network and a new anti-viral strategyNathaniel D Maynard
Department of Bioengineering, Stanford University, Palo Alto, California, United States of America
PLoS Genet 6:e1001017. 2010..Based on our data, it appears that 2-thiouridine modification of tRNAGlu, tRNAGln, and tRNALys is particularly important for the efficient production of infectious lambda phage particles...
- A whole-cell computational model predicts phenotype from genotypeJonathan R Karr
Graduate Program in Biophysics, Stanford University, Stanford, CA 94305, USA
Cell 150:389-401. 2012..We conclude that comprehensive whole-cell models can be used to facilitate biological discovery...
- Single-cell and population NF-κB dynamic responses depend on lipopolysaccharide preparationMiriam V Gutschow
Department of Bioengineering, Stanford University, Stanford, California, United States of America
PLoS ONE 8:e53222. 2013..The cellular response to lipopolysaccharide varies depending on the source and preparation of the ligand, however. Our goal was to compare single-cell NF-κB dynamics across multiple sources and concentrations of LPS...
- Reconciling gene expression data with known genome-scale regulatory network structuresMarkus J Herrgard
Department of Bioengineering, Bioinformatics Graduate Program, University of California, San Diego, La Jolla, California 92093 0412, USA
Genome Res 13:2423-34. 2003..The results suggest that targeted gene expression profiling data can be used to refine and expand particular subcomponents of known regulatory networks that are sufficiently decoupled from the rest of the network...
- Determining host metabolic limitations on viral replication via integrated modeling and experimental perturbationElsa W Birch
Chemical Engineering, Stanford University, Stanford, CA, USA
PLoS Comput Biol 8:e1002746. 2012..Taken together, these results emphasize the importance of considering viral infections in the context of host metabolism...
- WholeCellKB: model organism databases for comprehensive whole-cell modelsJonathan R Karr
Graduate Program in Biophysics, Stanford University, 318 Campus Drive West, Stanford, CA 94305, USA
Nucleic Acids Res 41:D787-92. 2013..WholeCellKB-MG is extensively cross-referenced to existing resources including BioCyc, KEGG and UniProt. WholeCellKB-MG is freely accessible through a web-based user interface as well as through a RESTful web service...
- Competing pathways control host resistance to virus via tRNA modification and programmed ribosomal frameshiftingNathaniel D Maynard
Department of Bioengineering, Stanford University, Stanford, CA, USA
Mol Syst Biol 8:567. 2012..Based on the universality of many key components of this network, in both the host and the virus, we anticipate that these findings may have broad relevance to understanding other infections, including viral infection of humans...
- Computational modeling of mammalian signaling networksJacob J Hughey
Department of Bioengineering, Stanford University, Stanford, CA, USA
Wiley Interdiscip Rev Syst Biol Med 2:194-209. 2010..Finally, we focus on three specific instances of 'model-driven discovery': cases in which computational modeling of a signaling network has led to new insights that have been verified experimentally...
- High-throughput, single-cell NF-κB dynamicsTimothy K Lee
Department of Bioengineering, Stanford University, 318 Campus Drive, Stanford, CA 94305, United States
Curr Opin Genet Dev 20:677-83. 2010..We highlight the major aspects of increasing throughput and describe a current system that can monitor, image and analyze the NF-κB activation of thousands of single cells in parallel...
- Transcriptional regulation in constraints-based metabolic models of Escherichia coliMarkus W Covert
Department of Bioengineering, University of California, San Diego, La Jolla, California 92093 0412, USA
J Biol Chem 277:28058-64. 2002..This combined metabolic/regulatory model is thus an important step toward the goal of synthesizing genome-scale models that accurately represent E. coli behavior...
- WholeCellViz: data visualization for whole-cell modelsRuby Lee
Department of Bioengineering, Stanford University, Stanford, CA 94025, USA
BMC Bioinformatics 14:253. 2013..However, discovering new biology from whole-cell models and other high-throughput technologies requires novel tools for exploring and analyzing complex, high-dimensional data...
- The virus as metabolic engineerNathaniel D Maynard
Department of Bioengineering, Stanford University, 318 Campus Drive, Stanford, CA 94305, USA
Biotechnol J 5:686-94. 2010..As a result, metabolic engineers have a unique perspective that could lead to novel and effective methods to combat viral infection...
- A noisy paracrine signal determines the cellular NF-kappaB response to lipopolysaccharideTimothy K Lee
Bioengineering Department, Stanford University, 318 Campus Drive West, Stanford, CA 94305 5444, USA
Sci Signal 2:ra65. 2009..Our findings show that mammalian cells can create "noisy" environments to produce diversified responses to stimuli...
- A dynamic network of transcription in LPS-treated human subjectsJunhee Seok
Department of Bioengineering, Stanford University, Stanford, California, USA
BMC Syst Biol 3:78. 2009..For example, Network Component Analysis (NCA) is an approach that can predict transcription factor activities over time as well as the relative regulatory influence of factors on each target gene...
- Constraints-based models: regulation of gene expression reduces the steady-state solution spaceMarkus W Covert
Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093 0412, USA
J Theor Biol 221:309-25. 2003..5 and 97.5%. The method developed here provides a way to interpret how regulatory mechanisms are used to constrain network functions and produce a small range of physiologically meaningful behaviors from all allowable network functions...
- Achieving stability of lipopolysaccharide-induced NF-kappaB activationMarkus W Covert
Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA
Science 309:1854-7. 2005..The MyD88-independent pathway required Inferon regulatory factor 3-dependent expression of TNFalpha to activate NF-kappaB, and the time required for TNFalpha synthesis established the delay...
- Integrating high-throughput and computational data elucidates bacterial networksMarkus W Covert
Bioengineering Department, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093 0412, USA
Nature 429:92-6. 2004..We find that a systems biology approach that combines genome-scale experimentation and computation can systematically generate hypotheses on the basis of disparate data sources...