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About Modeling T-Cell Activation Using Gene Expression Profiling and State Space Models
This document describes using state space models to analyze gene expression data from T cell activation experiments. State space models assume hidden state variables that evolve over time according to Markovian dynamics and influence observed gene expression measurements. The models were applied to time series gene expression data from T cell activation by stimuli bypassing the T cell receptor. The models provide testable hypotheses about genetic regulatory networks and interactions over time, with the goal of better understanding T cell activation signaling pathways.
Detailed Information
| Author: | ['Miguel Angel Castro'] |
|---|---|
| Publication Year: | 2016 |
| Pages: | 12 |
| Language: | English |
| Format: | |
| Price: | FREE |
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