Biological network inference is the process of making inferences and predictions about biological networks.[1] By using these networks to analyze patterns in biological systems, such as food-webs, we can visualize the nature and strength of these interactions between species, DNA, proteins, and more.
The analysis of biological networks with respect to diseases has led to the development of the field of network medicine.[2] Recent examples of application of network theory in biology include applications to understanding the cell cycle[3] as well as a quantitative framework for developmental processes.[4] Good network inference requires proper planning and execution of an experiment, thereby ensuring quality data acquisition. Optimal experimental design in principle refers to the use of statistical and or mathematical concepts to plan for data acquisition. This must be done in such a way that the data information content is enriched, and a sufficient amount of data is collected with enough technical and biological replicates where necessary.[citation needed]