With the spread of microarray and next-generation sequencing technologies, massive amounts of data can be collected. However, these collections of data require the use of "big data" data-mining techniques to extract the relevant information. These techniques are applied to biological data through bioinformatics studies. By applying these bioinformatics approaches to various omics datasets, the complex pathology of Alzheimer's disease (AD) has been substantially revealed. In this paper, we focus on the genomics- and transcriptomics-based studies, and review previous AD studies using these newer bioinformatics approaches.