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BooleaBayes Part 3- Using data to build a network for Small Cell Lung Cancer
We begin to look at how BooleaBayes, the computational tool developed in the Quaranta lab by David Wooten, PhD and me, can be applied to Small Cell Lung Cancer Data.
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BooleaBayes Part 2- Network Structure and Dynamics
This post takes a look what information we will need to gather in order to understand how cell identity is controlled.
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BooleaBayes Part 1- The Why
In this first post, I explain why we care about transcription factor networks and how they can help us treat Small Cell Lung Cancer.
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BooleaBayes Overview
This analysis was written to analyze transcription factor networks for Small Cell Lung Cancer phenotypes. I've written a primer on gene regulatory network dynamics and how our computational tool is able to define them and make predictions about the future using gene expression data-- RNA sequencing data that tells you the identity of a population of cells.
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What is Complexity?
Cancer acts as a complex system for some of the same reasons ant colonies do--tumors are made up of single cells, which are made up of relatively simpler components (proteins, DNA, RNA), which, at their heart, are just made up of chemicals, and yet the tumor system as a whole is able to devastate the human body.