The model is also able to represent endpoints that are not directly measured by the bioassay but derived from the measured endpoint. For example, based on the percentage response endpoint of a cell viability bioassay, a categorical value can be derived to indicate if this result is toxic/non-toxic. In this case, the value can be represented by a categorical endpoint class bao:BAO 0080045 which has a dimensionless unit obo:UO 0000186 and a string of the derived value. A gene-expression assay is an experimental method used to measure the activity of specific genes in a biological sample . For example, cells are treated with a compound of interest to perturb gene expression. A sample is prepared for each treatment concentration and measurements are taken at multiple time points. Moreover, multiple replicates of each sample are often included to account for technical variability and negative controls (e.g., untreated samples) are included to ensure that changes are due to experimental conditions. This design requires having a multi-level representation of the experiment components as shown in Figure . The measure group class bao:BAO 0000040 is semantically flexible which allows to describe such an experiment design. It facilitates the description of multiparametric assays that measure more than one effect of the perturbagen on the screened system. It also facilitates the definition of panel and profiling assays, e.g. assays that test compounds against multiple (gene/protein) targets. In this case, the bioassay has multiple measure groups, each of them representing a sample group of control or treatment of a specific concentration at a particular time point (the blue-colored sample group level in Figure ). Each sample group in turn has multiple measure groups, each of which represents a sample replicate (the yellow-colored sample level in Figure ). Moreover, a statistical analysis is carried out in gene-expression experiments to compare two sample groups and find the deferentially expressed genes (DEGs). Each comparison contrast is represented by a measure group that in turn links to two measure groups from the sample group level, the left side and right side of the contrast (the orange-colored differential gene expression contrast level in Figure ). Linked to each contrast measure group, all endpoints representing the individual average expression for sample genes. The endpoint representation of gene expression is the same as described in Figure , added to it, two derived endpoints, the fold change and p-value endpoints with dimensionless units and numerical values.