Table 2.
Databases for gene and protein interaction analyses.
| Application | Database | Description | Reference |
|---|---|---|---|
| DTI, PPI | Comparative Toxicogenomics Database | Information of chemicals, pathways, disease, organisms, genes, drug-gene interactions. Data are mainly collected from references. | 39,53 |
| Gene regulation and interaction | GEO (Gene Expression Omnibus) | One of NCBI databases. Gene expression data (eg. RNA, genome methylation and proteins) that comes from data submissions such as microarray or other researches. | 13 |
| Genomics of cancer | Cancer Genome Atlas (TCGA) | Cancer molecular data including genome, epigenome, transcriptome and proteome. | 38 |
| Biological pathway | GeneGo MetaBase | Bioinformatics including signaling and metabolic pathways, interactions among drugs and proteins as well as kinetic information of drugs. | 54,65 |
| PPI, DTI, signaling pathway | KEGG (Kyoto Encyclopedia of Genes and Genomes) | Information of pathways, genome, chemicals and diseases based on diagrams of interaction and reaction. It is complementary to the majority of the existing molecular biology databases that contain information on individual molecules or individual genes. | 12,40,44,72 |
| PPI | STRING (Search Tool for the Retrieval of Interacting Genes) | Functional links in PPI based on experimental data. Interactions are predicted by comparative genomics and text mining based on the scoring system. | 9,44,85 |
| Gene regulation and interaction | CCLE (the Cancer Cell Line Encyclopedia) | Gene expression data for human cancer analysis, including information of mutation, Gene Methylation and the associations between cell line and genomics. | 51,52,170 |
| DTI, DDI | PubChem (NCBI) | Characteristics of chemical molecules and activities from experimental results or literature. For drug analysis, it provides information on the chemical structure for each drug and the validated chemical depiction information. | 51,85,95 |
| Gene regulation and interaction | GO (Gene Ontology) | Biological annotations including structure, function and dynamics in pathways, molecules and organism level for a variety of species. | 19,35,44 |
| DTI | STITCH (search tool for interactions of chemicals) | Profiles of chemicals and proteins interactions. The data source includes experimental results and text mining. More than 9 million proteins come from almost 2,000 organisms in this database. | 39 |
| DTI | ChEMBL | Biological activities and characteristics of molecules such as chemicals and proteins that contribute to the study of drug target and drug discovery. | 54,54,86 |
| Gene regualtion and transcription | UniGene (NCBI) | Gene sequences from animals and plants. The well-characterized sequences are driven from algorithm-based classification which helps to identify uniqueness among genes. The Source of intact gene sequences is GenBank. | 13,74 |
| DTI, DDI | Drug Bank | Drug-target and drug-drug interacting information such as chemical sequence, three-dimensional structure and pharmacological pathway involvement. | 16,40,71,76 |
| Genomics of breast cancer | METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) | Clinical and expression data for breast tumors. The collected breast cancer specimens are grouped for discovery and validation. It helps to assess the survival prediction of cancer patients. | 173 |
| PPI | HPRD (Human Protein Reference Database) | Bioinformatics of human protein-protein interactions from literature and data are manually curated. | 33,42 |
| Signaling pathway | Reactome | Bioinformatics information including pathway, proteins and drugs for model visualization and analysis. | 9,29,44 |
| DDI | Online Mendelian Inheritance in Man (OMIM) | Disease data including disease loci, known disease genes and the known disorder-gene associations such as the molecular relationship between genetic variation and phenotypic expression. | 16,28 |
| PPI | Human Protein Reference Database (HPRD) | Protein information based on interactions described in published reports. The interaction set is expected to be biased toward known disease genes. | 15,33,42 |