Development and application of whole-cell computational models for science and engineering
Abstract/Contents
- Abstract
- A central challenge in biology is to understand how phenotype arises from genotype. Despite decades of research which have produced vast amounts of biological data, a complete, predictive understanding of biological behavior remains elusive. Computational techniques are critically needed to assemble this wealth of data into a unified theory. We have developed an integrative approach to computational modeling which enables comprehensive predictive models. We used this approach to construct the first "whole-cell" model. The model predicts the life cycle dynamics of the Gram-positive bacterium Mycoplasma genitalium from the level of individual molecules and their interactions, including its metabolism, transcription, translation, and replication. We validated the model by broadly comparing its predictions to a wide range of experimental data. We have demonstrated that the model can guide biological discovery including determining how the M. genitalium metabolic network can regulate the cell cycle, enumerating the modes of cellular death, and determining metabolic kinetic parameters. We have also demonstrated how whole-cell models can guide rational biological design. In addition, we have developed several software tools to facilitate whole-cell modeling, including databases for organizing training data and storing model predictions, and software for visually analyzing model predictions. Together, these technologies will accelerate bioengineering and medicine by enabling rapid in silico experimentation, facilitating experimental design and interpretation, and guiding rational biological design.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2014 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Karr, Jonathan Ross |
|---|---|
| Associated with | Stanford University, Biophysics Program. |
| Primary advisor | Covert, Markus |
| Primary advisor | Huang, Kerwyn Casey, 1979- |
| Thesis advisor | Covert, Markus |
| Thesis advisor | Huang, Kerwyn Casey, 1979- |
| Thesis advisor | Ferrell, James Ellsworth |
| Advisor | Ferrell, James Ellsworth |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Jonathan Ross Karr. |
|---|---|
| Note | Submitted to the Program in Biophysics. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2014. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2014 by Jonathan Ross Karr
- License
- This work is licensed under a Creative Commons Attribution 3.0 Unported license (CC BY).
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