While looking at these events in a time-sensitive and condition-specific manner is very important for deciphering CRM functionality, the dynamic behaviour of gene expression and CRM regulatory functionality can be considered only in the scope of gene regulatory networks [ 27].
Since this type of systematic bias is still unavoidable [ 40], some critical points are worthy of notice when using the epigenetic profiles for deciphering CRM functionality.
Part of the difficulty in deciphering the functionality of lncRNAs lies in their rapid evolution and the consequent reduction in levels of primary sequence conservation for lncRNAs among different organisms [ 33- 35].
When used in conjunction with enzymology and proteomics, this approach can assist in deciphering enzyme/protein functionality by comparing the metabolic profiles of a wild-type strain to those of an identical strain with a deletion in the genome corresponding to a gene coding for the specific enzyme/protein involved [ 19].
Numerous definitions of what a critical node 'is' have been previously investigated, including junctions in cell-signaling or protein-protein networks [1], highly influential individuals [2], smart grid vulnerability [3], targeted vaccination for pandemic prevention [4,5], or keys to decipher brain functionality [6].
Regarding that functional elements like macromolecular complexes interact at Golgi apparatus in distances far below light microscopic resolution, and that vesicles or cisternae of different compositions are homogenized during biochemical isolation or fractionation, it is obvious that high-resolution imaging technologies like cryo-electron microscopy are necessary to decipher Golgi functionality.
The utility of metagenomics approaches to deciphering such novel functionality in these systems is also highlighted.
In the current version of cisMEP, we aimed to deposit computationally identified CRMs and to provide epigenetic profiles for CRM prediction confidence assessment and potential CRM functionality deciphering.
Hence in deciphering the CRM functionality, users can also take care of the different cell types for data integration in order not to run the risk of deducing the incorrect inferences.
Hence understanding the temporal manner of CRMs are vital for deciphering the CRM regulatory functionality [ 27].
