Table 1.
Examples of functional biological information that can be represented using networks, along with corresponding databases/repositories and supplementary data analysis tools that can be used to assess the functional data in high-throughput omics datasets.
| Type of functional information | Select databases/ repositories | Supplementary Omic-data analysis tools |
|---|---|---|
| Metabolic pathways, reactions and associated enzymes and transporters | Kyoto Encyclopedia of Genes and Genomes (KEGG) (20) | MetaBridge (21) |
| Reactome (22) | OmicsPlayground (14) | |
| Panther pathway database (23) | ReactomePA (24) | |
| Gene Ontology (25) | SIGORA (26) | |
| Edinburg Human Metabolic Network (27) | iMAT (28) | |
| Recon3D (29) | INIT (30) | |
| iHsa (31) | mCADRE (32) | |
| BioModels (33) | TIMBR (31) | |
| Gene regulatory networks (interactions between transcription factors and their target genes) | Encyclopedia of DNA elements (ENCODE) (34, 35) JASPAR (36) TRANSFAC (37) |
MRNET (38) ARACNE (39) iRegulon (40) dynGENIE3 (41) |
| Protein-protein interaction (PPI) networks (includes direct, metabolic, and regulatory interactions) | International Molecular Exchange (IMEx) Consortium (42), which includes: InnateDB (43, 44) Biomolecular Interaction Network Database (BIND) (45) Database of Interacting Proteins (DIP) (46) Molecular INTeraction Database (MINT) (47) MIntAct (48) The Biological General Repository for Interaction Datasets (BioGRID) (49) |
NetworkAnalyst (50–52) OmicsNet (13) PPIExp (53) |
| Signaling networks (interactions involved in a cell's response to its environment) | KEGG (20) Reactome (22) STKE (54) TRANSPATH (55) |
ReactomePA (24) |
| Drug targets (interactions between drugs and their cellular targets) | DrugBank (56) Therapeutic target database (TTD) (57) SuperTarget (58) STITCH (59) ChEMBL (60) BindingDB (61) KEGG (20) |
DINIES (62) |