Scalable Reverse Engineering of Nonlinear Gene Networks
Current advanced molecular biology techniques provide gene expression (mRNA) levels of selected genes of an organism. In such aggregate, the mRNA level of one gene is mediated by the presence of specific proteins and metabolites produced by other genes. Gene Regulatory Networks (GRNs) include such structures, where a node (gene) is linked to others through gene-gene interactions. The developed algorithm is a new state-of-the-art process to infer GRNs, that is to find the gene-gene relationships from experimental mRNA levels. Knowledge of such interactions and so having possibility to act and control genes is important in biotech and pharmaceutical industries.