Table 3The representative approaches of bottom-up integrationMethod
Level of omics
Biological purpose
Mutation mRNA miRNA Modification Protein Metabolite Network Annotation
“eQTL-based” [
80
]
✓✓
eQTL-based analysis
TieDIE [
92
]
✓✓✓
Robust synthetize of signaling network
“Network-based”
[^79
]
✓✓✓
Identification of disrupted pathways
“Integrative network
analysis” [
114
]
✓✓✓
Identifying important genetic and
epigenetic features
“TCGA-based”
[^82
-^85
]
✓✓✓✓
Characterizing somatic alterations
“TCGA-based”
[^86
-^88
]
✓✓✓
Characterizing the genomic/epigenomic
landscape
“TCGA-based”
[^90
,^91
]
✓✓✓✓✓
Cancer subtypes caused by different
subsets of genetic and epigeneticabnormalities
“Generalizable
framework” [
81
]
✓✓
Identifying pathogenetically relevant
mutated genes
“Integrative
framework” [
89
]
✓✓✓
Determining the prognostic, predictive,
and therapeutic relevance of thefunctional proteome
“Pan-cancer
initiative” [
93
]
✓✓✓✓✓
The Cancer Genome Atlas pan-cancer
analysis project
dChip-GemiNI [
98
]
✓✓✓
Detecting feed-forward loops (FFLs) on
TF-miRNA-mRNA network
(continued)
Integrative Analysis of Omics Big Data 117