Metabolizer integrates three different pathway tools:

• Activity allows you to see how module activity changes in different conditions.
• Knockout allows you to simulate knock outs or over-expressions of one or several genes or the effect of a drug in metabolic module genes.
• Prediction allows you to train a prediction model and test it with different data.

Metabolizer is able to integrate RNA-Seq and microarray data to produce an accurate result.

Metabolizer allows you to compute a activity (overall flux) each metabolic module and each one of your data samples. Therefore, it allows you to compare the activity values:

• Between two groups, in order to see which module is changed and how

In order to check how to use these options please see Differential signaling.

Metabolizer allows you to train, download and test a prediction model for your dataset. Prediction can be done using following methods; LDA, SVM, Random Forest. The model can be trained either to:

• Discriminate between two different groups of samples, or
• Predict the value of an unknown variable.

In order to check how to use these options please see Prediction.