We introduce a gene-specific regularization factor when computing the Partial Correlation score to make the indeterminate regression feasible. We decided to slightly modify the computation of the sparse partial correlation matrix. Controlling for other genes’ expression we take into consideration additional biological sources, such as the PPI or co-occurrence in biological pathways, to prioritize which genes would have a greater weight, i.e., using a specific λ_(i,k) when computing partial correlations for gene i (gi) and controlling for gene k (gk). The higher the score in λ_(i,k) (for instance genes far away in the PPI) the less gk will be considered to regress gi expression.