Gene regulation in eukaryotes involves a complex interplay between the proximal promoter and distal genomic elements (such as enhancers) which work in concert to drive precise spatio-temporal gene expression. The experimental localization and characterization of gene regulatory elements is a very complex and resource-intensive process. The computational identification of regulatory regions that confer spatiotemporally specific tissue-restricted expression of a gene is thus an important challenge for computational biology. One of the most popular strategies for enhancer localization from DNA sequence is the use of conservation-based prefiltering and more recently, the use of canonical (transcription factor motifs) or de novo tissue-specific sequence motifs. However, there is an ongoing effort in the computational biology community to further improve the fidelity of enhancer predictions from sequence data by integrating other, complementary genomic modalities. In this work, we propose a framework that complements existing methodologies for prospective enhancer identification. The methods in this work are derived from two key insights: (i) that chromatin modification signatures can discriminate proximal and distally located regulatory regions and (ii) the notion of promoter-enhancer cross-talk (as assayed in 3C/5C experiments) might have implications in the search for regulatory sequences that co-operate with the promoter to yield tissue-restricted, gene-specific expression.