Biomarkers are used to predict quantitative metabolite concentration profiles in human red blood cells.. PLoS Comput Biol. 13(3):e1005424.. 2017.
COBRAme: A Computational Framework for Building and Manipulating Models of Metabolism and Gene Expression. bioRxiv.. 2017.
Global transcriptional regulatory network for Escherichia coli robustly connects gene expression to transcription factor activities.. Proc Natl Acad Sci U S A.. 2017.
Quantitative time-course metabolomics in human red blood cells reveal the temperature dependence of human metabolic networks.. J Biol Chem.. 2017.
Thermosensitivity of growth is determined by chaperone-mediated proteome reallocation. Proceedings of the National Academy of Sciences. 377121391183:201705524.. 2017.
Utilizing biomarkers to forecast quantitative metabolite concentration profiles in human red blood cells. 2017 IEEE Conference on Control Technology and Applications (CCTA).. 2017.
Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow.. Cell Syst.. 2016.
Reliable and efficient solution of genome-scale models of Metabolism and macromolecular Expression.. Sci Rep. 7:40863.. 2016.
solveME: fast and reliable solution of nonlinear ME models.. BMC Bioinformatics. 17(1):391.. 2016.