Integration of biological networks
Individual biological networks, including metabolic, regulatory , signalling and protein–protein interaction networks, have been used in the analysis of omics data and to reveal the underlying molecular mechanisms of diseases to discover novel biomarkers and drug targets. High- quality omics data, including transcriptomics, proteomics, metabolomics and fluxomics, enable the generation of high- quality metabolic, signalling and protein–protein interaction networks. As shown in the figure, the effects of transcription factors and proteins on other proteins can be predicted by integration of different biological networks, and the level metabolites can be measured as a metabolic fingerprint in different clinical conditions. For example, gene 1 (G1) is transcribed to transcript 1 (T1), which is translated to protein 1 (P1); P1 then acts on metabolite 1 (M1) in reaction 1 (R1) to generate metabolite 2 (M2).