Gene expression analysis

Abstract

Genome scale experiments routinely produce large data sets that require computational analysis, yet there are few student-based labs that illustrate the design and execution of these experiments. In order for students to understand and participate in the genomic world, teaching labs must be available where students generate and analyze large data sets. We present a microarray-based gene expression analysis experiment that is tailored for undergraduate students. The methods in this article describe an expression analysis experiment that can also be applied to CGH and SNP experiments. Factors such as technical difficulty, duration, cost, and availability of materials and equipments are considered in the lab design. The microarray teaching lab is performed in two sessions. The first is an introductory wet bench exercise that allows students to master the basic technical skills. The second builds on the concepts and skills with students acquiring and analyzing the microarray data. This lab exercise familiarizes students with large-scale data experiments and introduces them to the initial analysis steps.

Identifying the Salient Genes in Microarray Data: A Novel Game Theoretic Model for the Co-Expression Network

“…Along with contemporary sequencing tools, the microarray technique continues to be an exceptional methodology for large-scale expression analysis and concepts commonly used in genomic technologies. Microarrays can be utilized for conducting very high-end parallel tests of DNA, RNA, proteins, etc., for expression analysis, the detection of mutation, or re-sequencing [6]. Microarrays have an inherent capacity to spatially sort molecular species such that their concentrations can be autonomously estimated [7].…”