Biological Database Systems

Biological Database Systems

Denis Shestakov, University of Turku/Tampere

BioDB-1, ShestakovPage 2

Course Information

• Course structure:– Lectures: approx. 12 (plus today’s

intro and review lecture in the end of the course)

– Project work: details will be given next time

– Exam: easy to pass if project is done

– URL:


Course Information

• Dates:– Period 2: 27.11, 4.12, 11.12– Period 3: 10 meetings on

Mondays/Wednesdays

• Contact info:– Email: – ICT, B6019: at 15-18 on Tuesdays


Course Information: Literature• Slides• References in the end of slides• Books:

– Bioinformatics: Managing Scientific Data by Lacroix & Critchlow, Morgan Kaufmann, 2003 ISBN-10: 155860829X

– Database Systems Concepts, 5th edition by Silbershatz, Korth & Sudarshan, McGraw-Hill, 2005 ISBN-10: 0072958863

• Articles:– Biological database design and implementation

by Birney & Clamp (the Ensembl project), Briefings in Bioinformatics, 5(1):31-38, 2004

Biological Database Systems

1.1. Course Content1.2. Course Objectives1.3. Database and DBMS1.4. Biological Databases


Course content: main topics

1. Database concepts, database design process

2. Relational data model3. Introduction to SQL4. XML and XML-based databases5. Data structures for biological data:

storage and querying6. Model organism databases


Course content: main topics

7. LIMS, BioPostgres8. Analysis workflows, web services9. Integration of biological data10.Integration of biological data,

example of integration system11.Research issues in scientific

databases12.* Project discussion, exam

preparation


Course focus • Database issues:

– Biology-specific– Representation of biological data– Design of biological databases

• NOT about:– Usage of existing databases– Accessing/retrieving data from bio-

databases


Course goal

Give basic knowledge of biological* database design

* - for molecular biology


Do you need to know that?• Work in “wet” laboratory:

– One bioinformatician and many biologists– Likely to be IT guru for others– Expect to answer IT-related questions

• Work in bioinformatics lab:– Many bioinformaticians– Group may maintain several dbs– Basics are helpful

• Create/maintain biological databases– Start learning!– Ask for more information


Database?From Merriam-Webster dictionary:(http://www.merriam-webster.com/dictionary/database)


Database?• A collection of data:

– structured– searchable (i.e., indexable)– updated– cross-referenced

• Objective:– Transform “meaningless” raw data into useful

information which can be accessed and analysed in the best way

• Database Management System (DBMS):– software designed for the purpose of

managing databases (access, insert, delete, update, etc.)


DBMS

• A set of tools that:– Store– Extract– Modify

DatabaseDatabase

StoreStore ExtractExtract ModifyModify

USERSUSERS


Biological Databases?Explosive growth in biological data• E.g., tremendous increase in

nucleotide sequences (first increase in data due to the polymerase chain reaction (PCR) technique development in 1983)

• 1980: 80 genes fully sequenced• …


Biological Databases?• EMBL Database Growth:

Total nucleotides

(Nov 07: 188,490,792,445)Number of entries

(Nov 07: 106,144,026)


Biological Databases?

• Data (genomic sequences, 3D structures, 2D gel analysis, microarrays….) directly submitted to databases

• Essential tools for biological research, like reading relevant literature


Biological Databases: History

• 1965– Margaret Dayhoff et al. publish “Atlas

of Protein Sequences and Structures”• 1982

– EMBL initiates DNA sequence databases, followed within a year by GenBank and in 1984 by the DNA Database of Japan

• 1988– EMBL/GenBank/DDBJ agree on common

format for data elements


Biological Databases: some statistics• More than 1000 different databases

– 968 databases reported inThe Molecular Biology Database Collection: 2007 update by Galperin, Nucleic Acids Research, 2007, Vol. 35, Database issue D3-D4

– Metabase: database of biological databases, http://biodatabase.org/index.php/Main_Page

• Database sizes: <100kB to >100GB (EMBL >500GB)– DNA: >100GB– Protein: 1GB– 3D structure: 5GB

• Update frequency: daily to annyally• Freely accessible (as a rule)


Some databases in the field of molecular biology

AATDB, AceDb, ACUTS, ADB, AFDB, AGIS, AMSdb, ARR, AsDb, BBDB, BCGD, Beanref, Biolmage,BioMagResBank, BIOMDB, BLOCKS, BovGBASE,BOVMAP, BSORF, BTKbase, CANSITE, CarbBank,CARBHYD, CATH, CAZY, CCDC, CD4OLbase, CGAP,ChickGBASE, Colibri, COPE, CottonDB, CSNDB, CUTG,CyanoBase, dbCFC, dbEST, dbSTS, DDBJ, DGP, DictyDb,Picty_cDB, DIP, DOGS, DOMO, DPD, DPlnteract, ECDC,ECGC, EC02DBASE, EcoCyc, EcoGene, EMBL, EMD db,ENZYME, EPD, EpoDB, ESTHER, FlyBase, FlyView,GCRDB, GDB, GENATLAS, Genbank, GeneCards,Genline, GenLink, GENOTK, GenProtEC, GIFTS,GPCRDB, GRAP, GRBase, gRNAsdb, GRR, GSDB,HAEMB, HAMSTERS, HEART-2DPAGE, HEXAdb, HGMD,HIDB, HIDC, HlVdb, HotMolecBase, HOVERGEN, HPDB,HSC-2DPAGE, ICN, ICTVDB, IL2RGbase, IMGT, Kabat,KDNA, KEGG, Klotho, LGIC, MAD, MaizeDb, MDB,Medline, Mendel, MEROPS, MGDB, MGI, MHCPEP5Micado, MitoDat, MITOMAP, MJDB, MmtDB, Mol-R-Us,MPDB, MRR, MutBase, MycDB, NDB, NRSub, 0-lycBase,OMIA, OMIM, OPD, ORDB, OWL, PAHdb, PatBase, PDB,PDD, Pfam, PhosphoBase, PigBASE, PIR, PKR, PMD,PPDB, PRESAGE, PRINTS, ProDom, Prolysis, PROSITE,PROTOMAP, RatMAP, RDP, REBASE, RGP, SBASE,SCOP, SeqAnaiRef, SGD, SGP, SheepMap, Soybase,SPAD, SRNA db, SRPDB, STACK, StyGene,Sub2D,SubtiList, SWISS-2DPAGE, SWISS-3DIMAGE, SWISS-MODEL Repository, SWISS-PROT, TelDB, TGN, tmRDB,TOPS, TRANSFAC, TRR, UniGene, URNADB, V BASE,VDRR, VectorDB, WDCM, WIT, WormPep, YEPD, YPD, YPM, etc …

Find more at http://biodatabase.org


Categories of Biological Databases

1. Nucleotide sequences2. Genomics3. Mutation/polymorphism4. Protein seqiences5. Protein domain/family6. Proteomics (2D gel, MS)



7. Microarray8. Organism-specific9. 3D structure10.Metabolism11.Bibliography12.Others



7. Microarray8. Organism-specific9. 3D structure10.Metabolism11.Bibliography12.Others


Biological Databases: special features

• Autonomous: many independent maintainers

• Heterogeneous data formats: e.g., various data formats for the same data elements

• Dynamic: frequent and continous changes in data content (and, more importnatly, in data schema)

• Broad domain knowledge • Workflow-oriented: databases + rich set of

analysis tools• Information integration is essential:

aggregate data from several databases


Biological Databases: integration

Figure is taken from Bioinformatics: Managing Scientific Data by Lacroix & Critchlow, p.20

Business

Biological Database Systems