With a large genomic data set, the first thing a biologist will do is to look at the results from genes of interest. These genes may be involved in a project in the lab, or belong to a specific pathway, or just are genes that show significant change with treatment.
BxGenomicDB has powerful search functions to allow researchers to quickly identify genes of interest. If you know the gene symbol, description, or accession numbers, just type it in the search field. However, you can do a lot more. Here are some examples.
1) Differentially expressed genes. In this example, we are interested in genes that are highly expressed in metastasis cells vs. primary cells for prostate cancer. A typical filter for differential expression is to use 2 fold cutoff, and require corrected P-value to be less than 0.05.
2) Genes in a pathway that is differentially expressed. Let's look at another example. Here we are interested in genes involved in lipid metabolic process that are induced by fasting condition in liver, as well as induced by cAMP signaling. Since the data is analyzed by dChip, we will use Lower Fold Change at 90% confidence (LFC) more than 1.1 as the cutoff for differential expression.