CNGBdb hosts a vast amount of molecular data and other information that is indexed by CNGBdb Search. These data include literature, project, sample, experiment, run, assembly, variation, gene, protein, sequence et al.
On the homepage of CNGBdb, you can enter any meaningful word or number to find relevant information. For example, literature number (CNL_PMID24971553), gene name (TP53), species, disease, etc. CNGBdb supports word search. For example, if you search for "homo", it will return search results that match "homo" and will not return search results that match "ho" or "hom". More complex query syntax will be added in the CNGBdb iteration version.
Following the aforementioned query syntax, users can search according to data content and characteristics.
A few examples of queries that can be performed using CNGBdb Search are listed below.
Search for literature CNL_PMID24971553.
Search for gene TP53.
Search for protein Ovarian cancer-related protein 1.
Search for project CNP0000028.
Search for sample CNS0000027.
CNGBdb contains information on 10 data structures of project, sample, experiment, run, assembly, literature, variation, protein, sequence, gene. Searching by keyword on the homepage, all results in 10 data structures will be returned by default. On the page of search results, you can see the top 3 search results with the highest relevance of each sub database. If you want to view more results, click on “More results” below each sub database to view. Select one of the sub databases from the drop-down list on the left side of the search bar on the homepage to search, corresponding search results of the sub database will be returned. Scroll down the page, more search results up to 100 will be loaded, Search results after 100 will not be displayed. If the results you want are still not found in the 100 search results, it is recommended to modify the search terms to re-search.
Users can also re-search by inputting the search term through the search bar of the search result page, and the search bar of the search results page has the same function as the home search bar.
The navigation filter on the left allows users for a compact view and easy navigation across different databases. It provides a means for exploring the search results grouped in relevant databases and drilling down the scope of the results.
If you click on the number of a certain data, you can go to the details page of the data to view more detailed information. For example, click the literature number (CNL_PMID24971553) on the search result page to jump to the literature details page (/search/literature/CNL_PMID24971553/).
If you click on Related data for a particular entry you can explore its cross-references to other databases resources of CNGBdb, such as in the variation database of the search results, click on the gene in a certain data, you can link to the gene information page of the gene database.
CNGBdb search configures synonymous organisms (the synonym table is mainly from taxonomy database) and medical subject words (the synonym table is mainly comes from mesh). When you search for a keyword, the synonym of the keyword can also be retrieved, for example, Oryza sativa‘s scientific name is Oryza sativa L, Genbank common name is rice, Inherited blast name is monocots. When you search for Oryza sativa, all of its synonyms including Oryza sativa L, rice, monocots can also be retrieved.
The 10 data structures of CNGBdb support different search fields. The search fields are as follows.
|Literature||Literature ID, Title, Author, Journal, Publication type, Identifier(s), Abstract, Keywords|
|Gene||Gene ID, Identifier(s), Organism, Symbol, Title, Also knowns as|
|Variation||Variant ID, HGVS/Genome variation, Organism, Gene(s), Condition(s), Condition ID, Phenotype(s), Phenotype ID, Project ID, Literature ID, Identifier(s)|
|Protein||Protein ID, Protein name(s), Identifier(s), Entry name, Organism, Gene(s), Keywords|
|Sequence||Sequence ID, Gene(s), Identifier(s), Keywords, Literature ID, Molecule Type, Organism, Title|
|Project||Project ID, Accession in other database, Data type, Title, DOI|
|Sample||Sample ID, Accession in other database, Data type, Organism, Related accession, Sample name, Sample model, Organism ID|
|Experiment||Experiment ID, Accession in other database, Related accession, Platform, Title, Library name|
|Assembly||Assembly ID, Accession in other database, Related accession, Assembly name, Organism, Organism ID|
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20. Zou Y123,Xue W12,Luo G, et al. 1,520 reference genomes from cultivated human gut bacteria enable functional microbiome analyses. Nat Biotechnol,2019/2;37(2):179-185.
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26. Dynamics and Stabilization of the Human Gut Microbiome during the First Year of Life. Cell Host Microbe. 2015;17(6):852.
27. Zhang X, Zhang D, Jia H, et al. The oral and gut microbiomes are perturbed in rheumatoid arthritis and partly normalized after treatment. Nat Med. 2015;21(8):895-905.
28. Feng Q, Liang S, Jia H, et al. Gut microbiome development along the colorectal adenoma-carcinoma sequence. Nat Commun. 2015;6:6528. Published 2015 Mar 11. doi:10.1038/ncomms7528.
29. Yu J, Feng Q, Wong SH, et al. Metagenomic analysis of faecal microbiome as a tool towards targeted non-invasive biomarkers for colorectal cancer. Gut. 2015;66(1):70-78.
30. Xie H, Guo R, Zhong H, et al. Shotgun Metagenomics of 250 Adult Twins Reveals Genetic and Environmental Impacts on the Gut Microbiome. Cell Syst. 2016;3(6):572-584.e3.
31. Liu R, Hong J, Xu X, et al. Gut microbiome and serum metabolome alterations in obesity and after weight-loss intervention. Nat Med. 2017;23(7):859-868.
32. He Q, Gao Y, Jie Z, et al. Two distinct metacommunities characterize the gut microbiota in Crohn's disease patients. Gigascience. 2017;6(7):1-11.
33. Kuang YS, Lu JH, Li SH, et al. Connections between the human gut microbiome and gestational diabetes mellitus. Gigascience. 2017;6(8):1-12.
34. Jie Z, Xia H, Zhong SL, et al. The gut microbiome in atherosclerotic cardiovascular disease. Nat Commun. 2017;8(1):845. Published 2017 Oct 10. doi:10.1038/s41467-017-00900-1.
35. Gu Y, Wang X, Li J, et al. Analyses of gut microbiota and plasma bile acids enable stratification of patients for antidiabetic treatment. Nat Commun. 2017;8(1):1785. Published 2017 Nov 27. doi:10.1038/s41467-017-01682-2
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55. Li MM, Datto M, Duncavage EJ, et al. Standards and Guidelines for the Interpretation and Reporting of Sequence Variants in Cancer: A Joint
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6. HPO: https://hpo.jax.org/app/
7. CHPO: http://www.chinahpo.org/
The data archive services of CNGBdb include CNGB Nucleotide Sequence Archive (CNSA) , Pan immune repertoire database (PIRD) and GigaDB, which are committed to the submission, storage and sharing of data for biological sequencing research projects, samples, experiments, assembly, variations, etc. They’re designed to provide researchers around the world with the comprehensive data and information resources today, enabling researchers to use data with maximum authority.
The CNGBdb Scientific databases will build data applications in different fields based on the underlying data structures and data of CNGBdb, aiming to provide scientific data services for different research areas, such as biodiversity, microbe, cancer, immune, reproductive health, pathogen, etc., meet the needs of researchers in different fields, enhance the value of data, and promote data development and application.
Based on the underlying data, CNGBdb builds a distributed high-performance computing platform, and deploys application services such as BLAST, Cancer Data Analysis, Pathogen Identification.
Visualization is designed to visualize the biological data of CNGBdb using multiple visualization techniques, including the visualization of genomes, transcriptome, proteome and so on.
CNGB Data Access (CDA) provides users with the services of approval, authorization, and distribution of controlled data. Whether data is authorized for access is determined by the data owner/organization.
CNGBdb integrates data structures and standards of international omics, health, and medicine, such as The International Nucleotide Sequence Database Collaboration (INSDC), The Global Alliance for Genomics and Health GA4GH (GA4GH), Global Genome Biodiversity Network (GGBN), American College of Medical Genetics and Genomics (ACMG), and constructs standardized data standards and structures with wide compatibility.