Human

Gene expression regulators, such as transcription factors (TFs) and microRNAs (miRNAs), have varying regulatory targets based on the tissue and physiological state (context) within which they are expressed. While the emergence of regulator-characterizing experiments has inferred the target genes of many regulators across many contexts, methods for transferring regulator target genes across contexts are lacking. Further, regulator target gene lists frequently are not curated or have permissive inclusion criteria, impairing their use.

BioM2MetDisease is a manually curated database that aims to provide a comprehensive and experimentally supported resource of associations between metabolic diseases and various biomolecules. Recently, metabolic diseases such as diabetes have become one of the leading threats to people's health. Metabolic disease associated with alterations of multiple types of biomolecules such as miRNAs and metabolites.

DNA triplexes can naturally occur, co-localize and interact with many other regulatory DNA elements (e.g. G-quadruplex (G4) DNA motifs), specific DNA-binding proteins (e.g. transcription factors (TFs)), and micro-RNA (miRNA) precursors. Specific genome localizations of triplex target DNA sites (TTSs) may cause abnormalities in a double-helix DNA structure and can be directly involved in some human diseases. However, genome localization of specific TTSs, their interconnection with regulatory DNA elements and physiological roles in a cell are poor defined.

In recent years, a number of tools have been developed to explore microRNAs (miRNAs) by analyzing their target genes. However, a reverse problem, that is, inferring patterns of protein-coding genes through their miRNA regulators, has not been explored. As various miRNA annotation data become available, exploring gene patterns by analyzing the prior knowledge of their miRNA regulators is becoming more feasible.