Abstract Summary: We have developed MINOMICS, a tool that allows facile and in-depth visualization of prokaryotic transcriptomic and proteomic data in conjunction with genomics data. MINOMICS generates interactive linear genome maps in which multiple experimental datasets are displayed together with operon, regulatory motif, transcriptional promoter and transcriptional terminator information. Availability: MINOMICS is freely accessible at http://www.minomics.nl Contact: [email protected]; [email protected] Supplementary information: http://bioinformatics.biol.rug.nl/supplementary/minomics/

For most organisms, computational operon predictions are the only source of genome-wide operon information. Operon prediction methods described in literature are based on (a combination of) the following five criteria: (i) intergenic distance, (ii) conserved gene clusters, (iii) functional relation, (iv) sequence elements and (v) experimental evidence. The performance estimates of operon predictions reported in literature cannot directly be compared due to differences in methods and data used in these studies. Here, we survey the current status of operon prediction methods. Based on a comparison of the performance of operon predictions on Escherichia coli and Bacillus subtilis we conclude that there is still room for improvement. We expect that existing and newly generated genomics and transcriptomics data will further improve accuracy of operon prediction methods.