(a) providing a set of candidate yeast genes identified in a genome-wide screen of yeast genes in a yeast analogue of the physiologic or pathologic process of the animal;

(b) providing interactions between yeast genes comprising the candidate yeast genes of step (a);

(c) providing interactions between genes of the animal;

(d) determining a set of genes of the animal homologous to the set of candidate yeast genes;

(e) creating a model of the physiologic or pathologic process in the animal by augmenting interactions between the set of genes of the animal obtained in step (d) with gene interactions based on the interactions between yeast genes of step (b) homologous to the set of genes of the animal;

(f) identifying one or more gene or protein nodes of the model created in step (e) as a druggable target, and

(g) generating a cell having altered expression of the gene node identified as a druggable target or altered activity of a gene product of the gene node identified as a druggable tart,

wherein step (e), and optionally one or both of steps (b) and (c), comprises utilizing a computer system comprising one or more processors programmed to execute one or more computer-executable instructions which causes the computer system to perform the Prize-Collecting Steiner Forest (PCSF) algorithm to connect gene or protein nodes through genetic interactions, physical interactions and annotated pathways from one or more curated databases while minimizing costs to obtain a network, wherein the network is a representative network obtained by varying algorithm parameters to generate multiple networks and creating a representative network from the multiple networks with a maximum spanning tree algorithm.