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Distance Change Scaled Edit Distance Predicting Survival Time From Genomic Data

By Maria D. Gonzalez Gil and Mentor Larry Hall


The goal in this project is to take genomic data from a cancer tumor and determine where in the disease stage the patient may be, by looking at gene expression data set in which is applied the Traveling Salesman Problem (TSP) method and Probabilistic Ordering method to get the ordered data set. As result, we obtained from each method an ordering of the patients in the data set that should roughly be correlated with the survival time. What is wanted is to develop an ordering system using gene expression values in microarrays. Ideally, an ordering will be from longest to shortest surviving time. Problem One can look at gene expression data utilizing the hypothesis that the involved genes will continue to change expression levels in a consistent manner as cancer progresses and create a relative ordering. The problems are that there is no obvious measure to compare the orderings, and the sensitivity of the orderings to the set of gene expressions (e.g. gene set) used. Method Diagram From the microarray technique are obtained the genes expression level

Year: 2011
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