Gene regulatory networks (GRNs) describe epistatic relationship of genes and how the expression of some genes influence the expression of other genes. This information is critical for understanding molecular mechanisms regulating various biological processes and molecular basis of several diseases. Current research work mostly attempts to infer such regulatory relationships (and GRN architecture topology) from gene expression data. This paper improves on this methodology by utilizing additional information available that describes which cis-elements are present in which genes, and at what locations. Using the underlying principle that target genes of a transcription factor should share the same binding site in their promoter regions, we propose a scoring method that facilitates the refinement of a candidate GRN. Improvements are demonstrated with three data sets, on which GRNs are first obtained from existing dataset (AtRegNet) or using an existing approach (ARACNe), and then modified using cis-element information.