1. Organisation of databases and its major grouping
   1. Nucleotide Sequence Databases
      1. CEGA
         1. non-coding sequences
         2. highly conserved within various group of vertebrates
      2. JuncDB
         1. exon-exon junction sequences
      3. dbSUPER, SEA
         1. collect sequences of super enhancers
      4. DFam
         1. human DNA repeat families
      5. NPIDB
         1. nuclear-nuclear interaction
      6. ARESite
      7. Subtopic 7
      8. Subtopic 8
   2. RNA sequence databases
      1. Subtopic 1
   3. Protein sequence databases
   4. Structure Databases
   5. Genomics Databases (non-vertebrate)
   6. Metabolic and Signaling Pathways
   7. Human and other Vertebrate Genomes
   8. Human Genes and Diseases
   9. Microarray Data and other Gene Expression Databases
   10. Proteomics Resources
   11. Other Molecular Biology Databases
   12. Organelle databases
   13. Plant databases
   14. Immunological databases
   15. Cell biology
2. Online Updated Molecular Biology Database Collection 2016
   1. Nucleotide Sequence Databases
      1. CEGA
         1. non-coding sequences, highly conserved within various group
      2. JuncDB
         1. exon-exon junction sequences
      3. dbSUPER, SEA
         1. collect sequences of super enhancers
      4. DFam
         1. human DNA repeat families
      5. NPIDB
         1. nuclear-nuclear interaction
      6. ARESite
         1. AU-rich elements in vertebrate
      7. JASPAR, HOCOMOCO, ORegAnno and Regular DB
         1. transcriptional regulation
      8. BIGNAsim
         1. DNA dynamics based on molecular dynamics simulations
   2. Protein sequence databases
      1. Pfam
         1. sequence data
      2. UET
         1. predicted protein functional sites
      3. PDBe
         1. protein structure
      4. PDBFlex
         1. statistics of animation between pairs of homologous structure in PDB
      5. Gene3D
         1. function predictions to proteomes
      6. Fun Tree
         1. evolution of protein function in superfamilies
   3. Metabolic and Signaling Pathways
      1. KEGG, MetaCyc, Reactome, WikiPathways, ECMDB, BiGG Models and MNXref/MetaNetX
         1. metabolomics data, including metabolite standards, protocols, tutorials and analysis tools.
   4. Viruses, Bacteria, Protozoa and Fungi
      1. MG-RAST, EBI Metagenomics, probeBASE, and Human Pan-Microbe Communities
         1. metagenomics resources
      2. BacWGST
         1. identify the bacterial strains in samples isolated from infection
      3. Ensembl Genomes and Bacterial Diversity (BacDive)
         1. organizal genome diversity
   5. Genomes of Human and Model Organisms
      1. DMDD
         1. collects phenotypic data of mouse mutant embryos
      2. dbMAE
         1. provides manually curated data on allele-specific expression of autosomal genes
   6. Human Diseases and Drugs
      1. DIDA
         1. collects data of diseases
      2. ClinVar, GWASdb, HaploReg
         1. human genetic variation
   7. Plants
      1. IC4R
         1. all aspect of rice research
   8. mitochondrial and chemical compounds
      1. MitoCarta and MitoMiner
         1. mitochondrial proteins
      2. MitoAge
         1. mitochondrial DNA properties from various organisms
3. Numbers available
   1. 1685 database
      1. 15 categories
      2. 41 subcategories
4. Criteria for selection into NAR databases
   1. Nucleic acid therapeutics
   2. Intercellular communication via RNA-containing vesicles
   3. Functional roles of RNA modification
   4. Single cell gene regulation studies
   5. Nuclear architecture and functional consequences
   6. Gene targeting and genome engineering
   7. Molecular machines and complex molecular assemblages
   8. Single molecule studies of macromolecular function
5. References
   1. http://www.oxfordjournals.org/our_journals/nar/for_authors/criteria_scope.html
   2. http://www.oxfordjournals.org/nar/database/c/
6. Why we need to group these databases ?
   1. provide annotation for references
   2. narrow down search within BLD
   3. systematic to ease searching
7. Why databases are lose and dropped ?
   1. database are outdated
   2. no responsive
   3. content errors
8. Why databases are created and shared ?
   1. as a research tool
   2. to advance the utility of the Bioinformatics Links Directory
   3. to test effectiveness and improve any weaknesses
   4. make the collection better and more meaningful
9. Group Name
   1. SITI KHAIRUNNISA BINTI SALEH
   2. NUR SHAHIRAH AQILAH BT MOHD SHAFIE
   3. NURUL ATHIRAH BT ARIFIN
   4. NURUL NAJWA BT MOHD NASIR
   5. LADITAH DUISAN