The article discusses how scientists use statistical methods to find genes that are expressed differently in DNA microarray experiments. They test if genes have changed expression levels between conditions. They compare a null hypothesis (no change) to an alternative hypothesis (some change) and reject the null if there is enough evidence for the alternative. They also measure the chances of making mistakes, like falsely saying there is a change when there isn't (false positive) or missing a change that is there (power).