train_continuous_model: Train a linear model and predict the gene expression from an...
In CoRegFlux: CoRegFlux

Train a linear model and predict the gene expression from an experiment influence

1 2	train_continuous_model(train_expression, train_influence, minTarget = 10, experiment_influence, network)

`train_expression`	Gene expression of the training data set, not necessary if train_influence is supplied. Should be numerical matrix corresponding to the gene expression. Rownames should contain gene names/ids while samples should be in columns.
`train_influence`	Regulator influence scores of the train data set.
`minTarget`	The minimum number of targets for a regulator to be considered for actvity prediction when computing the influence. Default set to 10
`experiment_influence`	Regulator influence scores for the condition of interest as a named vector with the TF as names.
`network`	CoRegNet object to be interrogated for building the linear models