Statistical Mechanical Framework for Predicting Cellular Response

Statistical Mechanical Framework for Predicting Cellular Response

Developments in singe-cell analysis techniques allow simultaneous high-resolution measurements of cellular component copy number and variation within a cell population. These data provide a probability distribution for all possible states of the cell, as determined by the measured component copy num...

Full description

Bibliographic Details
Main Author: Forte, Lila
Format: Others
Published: 2016
Online Access:https://thesis.library.caltech.edu/9782/1/forte_lila_2016.pdf
Forte, Lila (2016) Statistical Mechanical Framework for Predicting Cellular Response. Master's thesis, California Institute of Technology. doi:10.7907/Z9K07273. https://resolver.caltech.edu/CaltechTHESIS:05272016-101847646 <https://resolver.caltech.edu/CaltechTHESIS:05272016-101847646>

Internet

https://thesis.library.caltech.edu/9782/1/forte_lila_2016.pdf
Forte, Lila (2016) Statistical Mechanical Framework for Predicting Cellular Response. Master's thesis, California Institute of Technology. doi:10.7907/Z9K07273. https://resolver.caltech.edu/CaltechTHESIS:05272016-101847646 <https://resolver.caltech.edu/CaltechTHESIS:05272016-101847646>

Similar Items