Introduction to Biological databases
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The document discusses biological databases. It begins by defining what a database is, including that it is a collection of related data organized in a way that allows information to be retrieved easily. It then discusses different types of biological databases, including those containing nucleotide sequences, protein sequences, 3D structures, gene expression data, and metabolic pathways. The rest of the document provides details on specific biological databases like GenBank, EMBL, DDBJ, and NCBI databases including Entrez. It emphasizes that biological data is heterogeneous, large in volume, dynamic and integrated across multiple databases.
![PRECISE RESULTS
MLH1[Gene Name] AND Human[Organism]](https://image.slidesharecdn.com/introductiontodatabases-210511074114/85/Introduction-to-Biological-databases-49-320.jpg)
Introduction to Biological databases
- 2. BIOLOGICAL DATABASES Dr. K. RameshKumar Assistant Professor PG & Research Dept. of Zoology Vivekananda College Tiruvedakam- West MADURAI - 625234
- 3. WHAT IS DATABASE? A database is any collection of related data. A Computerized archive used to store and organize data in such a way that information can be retrieved easily. A database is a collection of interrelated data store together without harmful and unnecessary redundancy (duplicate data) to serve multiple applications Retrieving is called firing a query
- 4. Structured collection of information. Consists of basic units called records or entries. Each record consists of fields, which hold pre- defined data related to the record. For example, a protein database would have protein entries as records and protein properties as fields (e.g., name of protein, length, amino-acid sequence)
- 5. THE ‘PERFECT’ DATABASE Comprehensive, but easy to search. Annotated, but not “too annotated”. A simple, easy to understand structure. Cross-referenced. Minimum redundancy. Easy retrieval of data.
- 7. BIOLOGICAL DATABASES Data Heterogeneity – diversity in the data types High Volume of data – highly heterogeneous- voluminous to support comprehensive investigation in various fields Uncertainty – Biological phenomena are observed and assumed to be true Data Curation – inconsistencies are due to a lack of knowledge in the desired field Large scale data integration – data collected from lab worldwide after years of research Data sharing – Scientific community examination and inspection Dynamic and subject to continual change – Everyday in various lab
- 8. BIOLOGICAL DATABASES Need for storing and communicating large datasets has grown Make biological data available to scientists. To make biological data available in computer- readable form.
- 11. DIFFERENT CLASSIFICATIONS OF DATABASES Type of data nucleotide sequences protein sequences proteins sequence patterns or motifs macromolecular 3D structure gene expression data metabolic pathways
- 12. DIFFERENT CLASSIFICATIONS OF DATABASES…. Primary or derived databases Primary databases: experimental results directly into database Secondary databases: results of analysis of primary databases Aggregate of many databases Links to other data items Combination of data Consolidation of data
- 13. DIFFERENT CLASSIFICATIONS OF DATABASES…. Availability Publicly available, no restrictions Available, but with copyright Accessible, but not downloadable Academic, but not freely available Proprietary, commercial; possibly free for academics
- 14. THE CENTRAL DOGMA & BIOLOGICAL DATA Protein structures -Experiments -Models (homologues) Literature information Original DNA Sequences (Genomes) Protein Sequences -Inferred -Direct sequencing Expressed DNA sequence ( = mRNA Sequences = cDNA sequences) Expressed Sequence Tag (ESTs)
- 16. NATIONAL CENTER FOR BIOTECHNOLOGY INFORMATION Created in 1988 as a part of the National Library of Medicine at NIH – Establish public databases – Research in computational biology – Develop software tools for sequence analysis – Disseminate biomedical information Bethesda,MD
- 17. WEB ACCESS: WWW.NCBI.NLM.NIH.GOV New Homepage Common footer New pages!
- 18. 18 NCBI AND ENTREZ One of the largest and most comprehensive databases belonging to the NIH – national institute of health (USA) Entrez is the search engine of NCBI Search for : genes, proteins, genomes, structures, diseases, publications and more. http://www.ncbi.nlm.nih.gov/
- 19. PRIMARY DATABASES This databases contains the raw nucleic acid sequence data which are produced and submitted by researchers worldwide. • Nucleic acid EMBL GenBank DDBJ (DNA Data Bank of Japan) • Protein PIR MIPS SWISS-PROT TrEMBL NRL-3D
- 20. NUCLEOTIDE SEQUENCE DATABASES EMBL, GenBank, and DDBJ are the three primary nucleotide sequence databases EMBL www.ebi.ac.uk/embl/ GenBank www.ncbi.nlm.nih.gov/Genbank/ DDBJ www.ddbj.nig.ac.jp They together constitute the International Nucleotide Sequence database callaboration.
- 21. GENBANK An annotated collection of all publicly available nucleotide and proteins Set up in 1979 at the LANL (Los Alamos). Maintained since 1992 NCBI (Bethesda). http://www.ncbi.nlm.nih.gov
- 24. EMBL NUCLEOTIDE SEQUENCE DATABASE An annotated collection of all publicly available nucleotide and protein sequences Created in 1980 at the European Molecular Biology Laboratory in Heidelberg. Maintained since 1994 by EBI- Cambridge. http://www.ebi.ac.uk/embl.html
- 25. DDBJ–DNA DATA BANK OF JAPAN An annotated collection of all publicly available nucleotide and protein sequences Started, 1984 at the National Institute of Genetics (NIG) in Mishima. Still maintained in this institute a team led by Takashi Gojobori. http://www.ddbj.nig.ac.jp
- 26. NCBI DATABASES AND SERVICES GenBank primary sequence database Free public access to biomedical literature PubMed free Medline (3 million searches per day) PubMed Central full text online access Entrez integrated molecular and literature databases
- 27. TYPES OF MOLECULAR DATABASES Primary Databases Original submissions by experimentalists Content controlled by the submitter Examples: GenBank, Trace, SRA, SNP, GEO Derivative Databases Derived from primary data Content controlled by third party (NCBI) Examples: NCBI Protein, Refseq, TPA, RefSNP, GEO datasets, UniGene, Homologene, Structure, Conserved Domain
- 28. PRIMARY VS. DERIVATIVE SEQUENCE DATABASES GenBank Sequencing Centers TATAGCCG TATAGCCG TATAGCCG TATAGCCG Labs Algorithms UniGene Curators RefSeq Genome Assembly TATAGCCG AGCTCCGATA CCGATGACAA Updated continually by NCBI Updated ONLY by submitters
- 29. SEQUENCE DATABASES AT NCBI Primary GenBank: NCBI’s primary sequence database Trace Archive: reads from capillary sequencers Sequence Read Archive: next generation data Derivative GenPept (GenBank translations) Outside Protein (UniProt—Swiss-Prot, PDB) NCBI Reference Sequences (RefSeq)
- 30. GENBANK - PRIMARY SEQUENCE DB Nucleotide only sequence database Archival in nature Historical Reflective of submitter point of view (subjective) Redundant Data Direct submissions (traditional records) Batch submissions FTP accounts (genome data)
- 31. GENBANK - PRIMARY SEQUENCE DB (2) Three collaborating databases 1. GenBank 2. DNA Database of Japan (DDBJ) 3. European Molecular Biology Laboratory (EMBL) Database
- 32. TRADITIONAL GENBANK RECORD ACCESSION U07418 VERSION U07418.1 GI:466461 Accession •Stable •Reportable •Universal Version Tracks changes in sequence GI number NCBI internal use well annotated the sequence is the data
- 34. FEATURES Location/Qualifiers source 1..2484 /organism="Homo sapiens" /mol_type="mRNA" /db_xref="taxon:9606" /chromosome="3" /map="3p22-p23" gene 1..2484 /gene="MLH1" CDS 22..2292 /gene="MLH1" /note="homolog of S. cerevisiae PMS1 (Swiss-Prot Accession Number P14242), S. cerevisiae MLH1 (GenBank Accession Number U07187), E. coli MUTL (Swiss-Prot Accession Number P23367), Salmonella typhimurium MUTL (Swiss-Prot Accession Number P14161) and Streptococcus pneumoniae (Swiss-Prot Accession Number P14160)" /codon_start=1 /product="DNA mismatch repair protein homolog" /protein_id="AAC50285.1" /db_xref="GI:463989" /translation="MSFVAGVIRRLDETVVNRIAAGEVIQRPANAIKEMIENCLDAKS TSIQVIVKEGGLKLIQIQDNGTGIRKEDLDIVCERFTTSKLQSFEDLASISTYGFRGE ALASISHVAHVTITTKTADGKCAYRASYSDGKLKAPPKPCAGNQGTQITVEDLFYNIA TRRKALKNPSEEYGKILEVVGRYSVHNAGISFSVKKQGETVADVRTLPNASTVDNIRS GENPEPT: GENBANK CDS TRANSLATIONS >gi|463989|gb|AAC50285.1| DNA mismatch repair prote... MSFVAGVIRRLDETVVNRIAAGEVIQRPANAIKEMIENCLDAKSTSIQVIV... EDLDIVCERFTTSKLQSFEDLASISTYGFRGEALASISHVAHVTITTKTAD...
- 35. REFSEQ: DERIVATIVE SEQUENCE DATABASE Curated transcripts and proteins Model transcripts and proteins Assembled Genomic Regions Chromosome records Human genome microbial organelle ftp://ftp.ncbi.nih.gov/refseq/release/
- 36. SELECTED REFSEQ ACCESSION NUMBERS mRNAs and Proteins NM_123456 Curated mRNA NP_123456 Curated Protein NR_123456 Curated non-coding RNA XM_123456 Predicted mRNA XP_123456 Predicted Protein XR_123456 Predicted non-coding RNA Gene Records NG_123456 Reference Genomic Sequence Chromosome NC_123455 Microbial replicons, organelle AC_123455 Alternate assemblies Assemblies NT_123456 Contig NW_123456 WGS Supercontig
- 38. REFSEQS: ANNOTATION REAGENTS Genomic DNA (NC, NT, NW) Model mRNA (XM) (XR) Curated mRNA (NM) (NR) Model protein (XP) Curated Protein (NP) Scanning.... = ? GenBank Sequences RefSeq
- 39. REFSEQ BENEFITS Non-redundancy Updates to reflect current sequence data and biology Data validation Format consistency Distinct accession series Stewardship by NCBI staff and collaborators
- 40. OTHER DERIVATIVE DATABASES Expressed Sequences dbSNP Structure Gene and more…
- 41. ENTREZ FINDING RELEVANT INFORMATION IN NCBI DATABASES
- 42. ENTREZ: A DISCOVERY SYSTEM Gene Taxonomy PubMed abstracts Nucleotide sequences Protein sequences 3-D Structure 3 -D Structure Word weight VAST BLAST BLAST Phylogeny Hard Link Neighbors Related Sequences Neighbors Related Sequences BLink Domains Neighbors Related Structures Pre-computed and pre-compiled data. •A potential “gold mine” of undiscovered relationships. •Used less than expected.
- 43. GLOBAL QUERY: ALL NCBI DATABASES The Entrez system: 38 (and counting) integrated databases
- 44. TRADITIONAL METHOD: THE LINKS MENU DNA Sequence Nucleotide – Protein Link Related Proteins Protein – Structure Link 3-D Structure
- 45. THE PROBLEM Rapidly growing databases with complex and changing relationships Rapidly changing interfaces to match the above Result Many people don’t know: Where to begin Where to click on a Web page Why it might be useful to click there
- 46. GLOBAL NCBI (ENTREZ) SEARCH colon cancer
- 47. GLOBAL ENTREZ SEARCH RESULTS
- 48. ENTREZ TIP: START SEARCHES IN GENE Other Entrez DBs HomoloGene Entrez Protein Gene UniGene BLink Homologene: Gene Neighbors
- 49. PRECISE RESULTS MLH1[Gene Name] AND Human[Organism]
- 50. MLH1 GENE RECORD
- 52. GENEVIEW: HUMAN MLH1 VARIATIONS ATPase domain
- 53. ‘TAKE HOME MESSAGE’ ADVANTAGES OF DATA INTEGRATION More relevant inter-related information in one place Makes it easier to find additional relevant information related to your initial query Potentially find information indirectly linked, but relevant to your subject of interest uncover non-obvious genetic features that explain phenotype or disease Easier to build a ‘story’ based on multiple pieces of biological evidence