Understanding how complex phenotypes arise from individual molecules and their interactions is a primary challenge in biology that computational approaches are poised to tackle. We report a whole-cell computational model of the life cycle of the human pathogen Mycoplasma genitalium that includes all of its molecular components and their interactions. An integrative approach to modeling that combines diverse mathematics enabled the simultaneous inclusion of fundamentally different cellular processes and experimental measurements. Our whole-cell model accounts for all annotated gene functions and was validated against a broad range of data. The model provides insights into many previously unobserved cellular behaviors, including in vivo rates of protein-DNA association and an inverse relationship between the durations of DNA replication initiation and replication. In addition, experimental analysis directed by model predictions identified previously undetected kinetic parameters and biological functions. We conclude that comprehensive whole-cell models can be used to facilitate biological discovery.
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About the speaker:
Markus Covert's main interests focus on integrating experimental and computational approaches to study large biological systems. He began his career with Bernhard Palsson, working in metabolic and transcriptional regulatory modeling of Escherichia coli, and became the first graduate of the Bioinformatics program at UCSD with a combined degree in Bioengineering and Bioinformatics. He then became a postdoctoral fellow with David Baltimore at Caltech, where he used a combined experimental/computational approach to study the NF-kappaB signaling network. He started as an Assistant Professor in Stanford's Bioengineering Department in January 2007, and won the NIH Director's Pioneer Award for transformative research in 2009.
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