Rank aggregation refers to the task of combining different orderings of an identical set of objects to obtain a consensus ranked list. Other than meta-search in web mining, in last few years, this technique has successfully been employed to address problems arising from bioinformatics domain. Consensus ranking of disease related genes, miRNA targets are ample examples in this context. It can be argued that scores are more informative than mere ranks. Existing score based aggregation techniques are evolutionary in nature and consume significant amount of time. We, for the first time propose a Markov chain for score based aggregation ranked lists. The proposed method is found out-performing the existing methods in terms of time consumption (by far) and performance when used in context of microRNA (miRNA) target ranking.