LAUSR

Ranking the metabolites towards the corresponding diseases is the fast-growing technique in the field of drug discovery. In this article, a novel method subcellular localization weight-based MiRNA similarity (SLWBMISM) which is equipped to find the metabolite similarity among the metabolites and InfDisSim method is equipped to calculate the disease similarity. And finally, the random walk algorithm is used to rank the priority of metabolites on particular diseases. The experimental dataset used in this research work has been downloaded from the online web portal Human Metabolome Data Base. After extracting the disease as well as metabolites, the above said algorithms are used to find the similarities and for ranking the metabolites. Totally 1955 metabolites and 581 diseases are considered as an experimental dataset. The proposed research work extracted 31,05,028 similarities in which 8,89,408 similarities were considered as for the experiment and the rest of them are considered as outliers. From these experiments, there are more interactions found out as it is used to identify the relationships among the metabolites and novel relationship has been identified.