Title :
Finding Discriminatory Genes: A Methodology for Validating Microarray Studies
Author :
Khan, Sharifullah ; Greiner, Russell
Author_Institution :
Dept. of Comput. Sci., Univ. of Alberta, Edmonton, AB, Canada
Abstract :
This paper explores the challenge of efficiently collecting data to find which genes (from a given set of candidates) are differentially expressed. We consider several algorithms for this task, including some that assume there are only two types of genes: those that are not differentially expressed, and those that are differentially expressed to the same level. We provide a framework for evaluating such algorithms and also present an algorithm that has nice theoretical properties and performs very well on both real and simulated data.
Keywords :
bioinformatics; data analysis; genetics; molecular biophysics; bioinformatics; data collection; discriminatory genes; gene differential expression; microarray studies; Algorithm design and analysis; Gaussian distribution; Gene expression; Manganese; Prediction algorithms; Probes; Resource management; Biomarker Discovery; Microarray Analysis; Sequential Design;
Conference_Titel :
Data Mining Workshops (ICDMW), 2013 IEEE 13th International Conference on
Conference_Location :
Dallas, TX
Print_ISBN :
978-1-4799-3143-9
DOI :
10.1109/ICDMW.2013.122
