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We propose a new method for measuring the semantic similarity of genes based on path length between their annotation terms in the gene ontology. Our method applies an exponential transfer function to the average path length between two genes to compute their similarity. The non-linear measure ensures that the semantic similarity decreases with distance and proves to be quite competitive when compared to other measures. The advantage of the proposed measure is its simplicity and ease of implementation which gives it a great appeal in this domain. The measure uses only one feature (path length) for computing the similarity between genes. For validation purposes, we computed the similarity of genes from the Saccharomyces genome database (SGD) taking part in various cellular pathways. We analyzed 152 pathways from SGD and compared our similarity results with two of the leading measures. The proposed measure proved to be very competitive in all cases and the clustering results showed that our method is able to surpass the leading methods in certain cases.