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About

Database Commons is a curated catalogue of biological databases, providing people with easy access to a comprehensive collection of publicly available biological databases encompassing different data types and spanning diverse organisms. It integrates relevant information for all collected databases (including database name, URL, description, hosted institution, related publication(s), contact information, etc.) and catalogues each database based on its data type, organism and locating, accordingly enabling people to easily find a specific collection of databases of interest.

Database Commons allows any one to rate any database by considering data quality & quantity, content organization & presentation, and system accessibility & reliability, facilitating efficient location of appropriate databases of interest.

Together, Database Commons features cataloguing databases under different criteria and incorporating community rating on database utility, thus serving as a valuable resource for effective exploitation of all publicly available databases.

To date, databases in Database Commons are collected primarily from journals including Nucleic Acid Research, Database, Bioinformatics, BMC Bioinformatics, etc.


Data Type

A database may encompass multiple data types. In Database Commons, there are a total of 4 data types as detailed below.

  1. DNA: gene/chromosome/genome sequence, DNA mutation/modification, DNA structure, DNA elements including probe, primer, motif, repeat sequence, etc.
  2. RNA: RNA sequence, coding & non-coding transcripts, alternative splicing, RNA editing/modification, RNA probe and primer, RNA motif and structure, RNA expression
  3. Protein: protein sequence, protein motif and domain, protein structure, protein modification, protein-protein interaction, protein expression
  4. Other chemical compound: chemical compound except nucleic acid and protein

Category

  1. DNA Raw bio-data: raw data of nucleic acid/protein sequencing and microarray, and image, digit, video, audio from biological and medical research
  2. Gene, genome and annotation: gene/genetic element annotation, gene structure/family/motif/domain annotation, genome annotation, comparative genome (metagenome, pan-genome) analysis and annotation
  3. Genotype, phenotype and variation: genotypes, phenotypes, multiple-scale variations (including SNP, INDEL, CNV, chromosomal rearrangement and other structural variation), genotype-phenotype associations
  4. Phylogeny and homology: phylogeny reconstruction of genes/species, evolutionary history/process/event among individuals/organisms, homology identification
  5. Expression: RNA/protein expression, expression abundance and pattern, RNA probe or primer used for gene expression detection, differential expression analysis
  6. Modification: DNA modification, post-transcriptional modification of mRNA and non-coding RNA, post-translational modification of protein, modification type/technology/function
  7. Structure: secondary, tertiary and quaternary structure of DNA/RNA/protein, chromatin structure
  8. Interaction: direct (physical) and indirect (functional) associations, including protein-protein interaction, RNA-protein interaction, DNA-protein interaction, gene regulatory interaction, biochemical reaction, antigen and antibody, and genetic interaction
  9. Pathway: biological pathways for metabolic, signaling, gene regulatory analysis
  10. Health and medicine: disease variation/genotype-phenotype association, immune reaction, disease model, clinical biomarker, therapeutic target, drug & chemical compound, pharmacogenomics and pharmacodynamics, electronic health record
  11. Standard, ontology and nomenclature: standard, ontology and nomenclature for biological entities
  12. Literature: literature information, literature/text mining, textual annotation based on literature
  13. Metadata: metadata information for biological entities, e.g., project/sample/experiment/run/database/tool

Community Rating

Database Commons features community rating on database utility by taking account of the following three criteria.

  • Data quality & quantity: consider data integrity, accuracy, standardization, consistency and comprehensiveness
  • Content organization & presentation: consider whether content is organized in an appropriate manner which makes content easily readable and understandable and is presented by user friendly web interface
  • System accessibility & reliability: consider whether system is always accessible and reliably working

A database containing high-quality curated data is abortive if data is poorly organized or presented.

A database containing high-quality curated data is unavailing if this database cannot be accessible or reliably working.


HTTP Status Codes

Here is a list of HTTP status codes with a brief explanation, which are represented by three digits and fall into five classes.

  • 1xx Informational: e.g., 101 Switching Protocols
  • 2xx Success: e.g., 200 OK, that is standard response for successful HTTP requests.
  • 3xx Redirection: e.g., 301 Moved Permanently
  • 4xx Client Error: e.g., 403 Forbidden, 404 Not Found
  • 5xx Server Error: e.g., 500 Internal Server Error, 503 Service Unavailable

More information about HTTP status code can be found at Wikipedia.

In addition, unexpected exceptions including timeout, errors occurred when sending requests, etc., are indicated by "-1".


Contact Information

BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences
No.1 Beichen West Road
Chaoyang District, Beijing 100101
China

Email: Dr. Lina Ma (malina (AT) big.ac.cn), Dr. Zhang Zhang (zhangzhang (AT) big.ac.cn)
Tel: +86 (10) 84097845
Fax: +86 (10) 84097298