NAR Database

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NAR Database by Mind Map: NAR Database

1. Online Updated Molecular Biology Database Collection 2016

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 clasification of DNA-protein complexes

1.1.7. JASPAR, HOCOMOCO, ORegAnno, RegulonDB Transcriptional regulation

1.1.8. BIGNAsim DNA dynamics- molecular dynamics simulations

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 Signaling Pathways

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

1.4. 4. Viruses, Bacteria,Protozoa and Fungi

1.4.1. MG-RAST, EBI Metagenomics & 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 expression 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 ClinVar, GWASdb, HaploReg human genetic variation resources on patented drugs, potential drug targets side effects, withdrawn drugs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

1.8.2. MitoAge mitochondrial DNA properties from various organisms

2. Numbers available

2.1. total : 1685 databases

2.1.1. 88 new resources

2.1.2. 23 removed obsolete websites

3. Why we need to group these databases?

3.1. large number of databases makes bioinformatics researcher difficult to track their database within their own specific area

3.2. ease of search

3.3. aim to provide structural annotation

3.4. rapid publication of papers by following categories

3.5. allowed users to narrow down the possible links they needed

4. References

4.1. 1. 2. 3. Galperin, Michael Y. “The Molecular Biology Database Collection: 2007 Update.” Nucleic Acids Research 35.Database issue (2007): D3–D4. PMC. Web. 4 Mar. 2016. 4. Rigden, Daniel J., Xosé M. Fernández-Suárez, and Michael Y. Galperin. "The 2016 database issue of Nucleic Acids Research and an updated molecular biology database collection." Nucleic acids research 44.D1 (2016): D1-D6. 5. 6.

5. Online Molecular Biology Databases Collection

5.1. 1. Nucleotide Sequence Databases

5.2. 2. RNA Sequence Databases

5.3. 3. Protein Sequence Databases

5.4. 4. Structure Databases

5.5. 5. Genomics Databases(Non-Vertebrate)

5.6. 6.Metabolic and Signaling Pathways

5.7. 7. Human and other Vertebrate Genomes

5.8. 8. Human Genes and Diseases

5.9. 9. Microarray Data and other other Gene Expression Databases

5.10. 10.Proteomics Resourses

5.11. 11. Others Molecular Biology Databases

5.12. 12. Organelle Databases

5.13. 13. Plant Databases

5.14. 14. Immunological Databases

5.15. 15. Cell Biology

6. Why databases are created and shared?

6.1. Make biological data available to scientists

6.1.1. not all data is actually published explicitly in a single article eg . genome sequences

6.1.2. search for all data very time-consuming

6.1.3. publish data maybe difficult to find or access in one single place eg. book, site, database

6.2. To make biological data available in computer-readable form

6.3. need for storing and communicating large datasets has grown tremendously

6.4. convenient method for storing, searching and retrieving necessary data

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

7.1. superseded by newer and more advanced databases

7.1.1. Crow21

7.1.2. PIR-NREF

7.2. the database is no longer own by its former organization

7.2.1. INFOBIOGEN HugeMap GenetPig DbCat

7.3. database is migrated to new website


7.4. tightening of budget

7.4.1. ExDom databases of exon-intron structure of the genes in seven eukaryotic genome has to be removed because it does not provide free version anymore

8. Group 1 Group member: 1. Hang Bee Wen 2. Yong Jing Xuan 3. Ngooi Chen Yi 4. Tang Pui Yen 5. Ooi Zhi Sin

9. Criteria for selection into NAR database

9.1. 1. Longevity and sustainability value

9.2. 2. Uniqueness of the databases

9.3. 3. Databases originality

9.4. 4. Scientific excellence and significance in research

9.5. 5. General utility of the database to the scientific community, comprehensiveness of coverage and degree of value added in the production of databases

9.6. 6. Web-accessible databases that offer carefully curated data that are not available elsewhere

9.7. 7. Free accessible