The goal of Gene Normalization (GN) is to identify the unique database identifiers of genes and proteins mentioned in biomedical literature. A major difficulty in GN comes from inter-species gene ambiguity. That is, the same gene name can refer to different database identifiers depending on the species in question. In this paper, we introduce a method to exploit contextual information in an abstract, like tissue type, chromosome location, etc., to tackle this problem. Using this technique, we have been able to improve system performance (F-score) by 14.3% on the BioCreAtIvE-II GN task test set.