NAR DATABASES

1. Online Updated Molecular Biology Database Collection

1.1. 1. Nucleic Acid Sequence and Structure

1.1.1. -CEGA: Highly conserved groups of vertebrates. (potential promoters, enhancers, and other regulatory elements)

1.1.2. JuncDB: exon-exon junction sequences

1.1.3. dbSUPER, SEA: sequences of super-enhancers

1.1.4. Dfam: human DNA repeat families

1.1.5. ARESite: AU-rich elements in vertebrates UTRs

1.1.6. -NPIDB: nuclear-protein interaction database-proposes classification of DNA-protein complexes

1.1.7. JASPAR, HOCOMOCO, ORegAnno, RegulonDB: Transcriptional regulation

1.1.8. BIGNAsim: DNA dynamics- molecular dynamics simulation

1.2. 2. Protein Sequences and Structure

1.2.1. ELM,NBDB,UET: predicted protein functional sites

1.2.2. sORE: proteomics database-ribosome profiling

1.2.3. PRIDE, dbPTM: updates on databases on proteomic peptide identification and post-translational modifications

1.2.4. PDBe: improve the value added to and accessibility of protein structure significantly

1.3. 3. Metabolic and Signalling pathways

1.3.1. KEGG,MetaCyc, Reactome, WikiPath, ECMDB, BiGG Models, MNXref/MetaNetX: Metabolomics data- metabolite standards, protocols, tutorials and analysis tools

1.4. 4. Viruses, Bacteria, Protozoa and Fungi

1.4.1. MG-RAST, EBI Metagenomics and probeBASE, Human Pan-Microbe Communities: metagenomics resources

1.4.2. BacWGST: identifying bacterial strains in samples isolated from infection

1.4.3. Ensembl Genomes, Bacterial Diversity (BacDive): organizational genome diversity

1.5. 5. Genomes of Human and Model Organisms

1.5.1. DMDD: Collects phenotypic data of mouse mutant embryos

1.5.2. dbMAE: allele-specific expressions of autosomal genes, transcriptional activity of two alleles epigenetically controlled.

1.6. 6. Human Diseases and Drugs

1.6.1. ClinVar,GWASdb, HaploReg: human genetic variations, resources on patented drugs, potential drug targets, sites effect, withdrawn drugs.

1.7. 7. Plants

1.7.1. -IC4R: all aspects of rice research

1.8. 8. Others (Mitochondrial and Chemical Compounds)

1.8.1. MitoCarta, MitoMiner: mitochondrial proteins

2. Numbers Available

2.1. Total: 1685 databases

2.2. 88 new resources added

2.3. description of 62 newly created databases

2.4. updated on 95 existing databases in NAR

2.5. 17 decribed elsewhere

2.6. 121 non-responsive databases

2.7. 23 obsolete websites removed

3. Criteria for selection into NAR database.

3.1. 1. Various type of databases e.g. protein database & nucleic acid database.

3.2. 2. Resources provided by three major bioinformatics centers, the U.S. National Center for Biotechnology Information (NCBI), the European Bioinformatics Institute (EMBLEBI) and Swiss Institute for Bioinformatics (SIB).

3.3. 3. Always updated and provide recent article research

3.4. 4. Can be accessed by any researcher.

3.5. 5. The article must be scientific .

4. Why we need to group these databases?

4.1. 1. To search article easily

4.2. 2. To avoid redundancy due to rapid publication of articles within its specific discipline.

4.3. 3. The overflowing articles are merged. Search result can be narrowed down, thus the article needed is easy to search

5. why some databases are no longer in the the databases and dropped from it.

5.1. Lot of data cause redundant of data

5.2. outdated databases

5.3. Database cannot be function properly

6. why databases are created and shared.

6.1. To gain profit

6.2. Can stored lot of data and it will be organize

6.3. That data can be accsess by many user and can be update e.g Wikipedia