Figure 1

Construction of the machine-learning model to predict EC numbers. (1) Test dataset: DSs and EC numbers for every enzyme were extracted from original datasets, such as Swiss-Prot. (2) These proteins were categorized into groups based on common DSs. Subsequently, the groups were divided into subgroups based on the corresponding EC numbers. Thus, the numbers in each cell represent the number of proteins in each subgroup, and the total member number for each group is summarized in the last row. The numbers of dominant subgroups within one group are colored red. (3) The abundance of each subgroup within its parent group (the same DS) was calculated and represented. The abundance of dominant subgroups for each group (the same DS) is colored red. (4) Prediction model: Every DS was associated with the relevant dominant EC number within its protein group (carrying this DS). The abundance of dominant EC subgroups was extracted and set as the “specificity” for this EC-DS pair.