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Bio sql presentation
The document discusses BioSQL, a generic relational data model for storing biological data in a relational database. It provides an overview of the BioSQL schema, which defines standardized relation types to store entities like biological entries, sequences, sequence features, annotations, ontologies, and taxonomic information. The data model aims to provide a flexible yet standardized storage solution and is compatible with various programming languages. However, it is best suited for single-user installations and does not consider aspects like protein structure prediction.
Bio sql presentation
- 1. BioSQL: A Genericrelational model for Bioinformatics BI-691
- 2. Generic Data ModelOverviewof BioSQL SchemaPreface of BioSQLDependency of BioSQLIntroductionInstallation BioSQL
- 3. Application of BioSQLAdvantagesof BioSQLLimitation of BioSQLConclusionReferences
- 4. For database managementRelational model is very important Conceptualization of real world thing into logical model First formulated and proposed in 1969 by Eadger F. Codd Logical model is use making relation and their relationship
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- 6. This model isrepresented in terms of tuples, grouped into relations A database organized in terms of the relational model is a relational database Relational data model is the primary data model This used widely around the world for data storage and processing
- 9. The generic datamodel is the generalization of the conventional data model This generic data model defines the standardised relation types Consensus among the different Relational Modeler of can produce a generic model of a particular domain
- 11. Generic Data Model EwanBirney started BioSQL in 2001 Major Redesign and Refactorings 2002-2003 PhyloDb module added at 2006 V1.0 released in March 2008
- 12. Not a QueryLanguage, It is a schema/dbmodel!!!
- 13. Covering sequences, features,sequence and feature annotation, a reference taxonomy, and ontologies Required highly normalized relational model Local storage of global biological data
- 15. BioSQL schema isnot strongly typed paradigm Derived entity always is in object oriented sense Weakly typed paradigm Generic, but can hold any number of specialization
- 16. Annotation Bundle Seqfeature With location And Annotation Ontology term and Relationship Bioentrywith taxon and names spaces
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- 18. Core entity ofBioSQL Track any single entry or record in a biological databases The BIOENTRY contains information about the record's public name, public accession and version
- 19. A BIODATABASE issimply a collection of bioentries one BIOENTRY may only belong to one BIODATABASE one BIODATABASE may contain many bioentries
- 20. In BioSQL, allrelation have bioentries BIOSEQUENCE table contains the raw sequence information associated with a BIOENTRY Alphabet information ('protein', 'dna', 'rna') One to One Relationship with BIOENTRY
- 21. BIOENTRY may themselvesbe related to one another (e.g., a PDB record may be composed of multiple subrecords for separate chains)
- 22. Basic taxonomic informationabout the organism to which a given BIOENTRY refers Reflect the structure of NCBI's taxonomy database Each BIOENTRY can be associated with only one taxon Many BIOENTRY can be associated with the same taxon
- 23. Annotation Bundle Seqfeature With location And Annotation Ontology term and Relationship Bioentrywith taxon and names spaces
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- 25. Semantic of SequenceDescribing the stop and start coordinates and strand
- 26. Annotation Bundle Seqfeature With location And Annotation Ontology term and Relationship Bioentrywith taxon and names spaces
- 27. Ontology term and RelationshipTermRelationTermTerm SynonymTermdbxrefOntology
- 28. Term is usedto "label" a seqfeature's name An ontology is essentially a dictionary of terms in a somewhat-controlled vocabulary
- 29. Annotation Bundle Seqfeature With location And Annotation Ontology term and Relationship Bioentrywith taxon and names spaces
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- 31. Annotation Bundle Seqfeature With location And Annotation Ontology term and Relationship Bioentrywith taxon and names spaces
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- 44. The BioSQL projectprovides a well thought out relational database schema for storing biological sequences and annotations Advantages of reusability Compatible with several programming languages like BioPython, BioPerl, BioJava, BioRuby etc Flexible storage of data via a key/value pair model
- 45. Extensible with therequired situation Overall data model based on GenBank flat files It also allows great flexibility in choosing the data used by Snapshot since sequence data from any source, including online databases locally generated sequence data can be added
- 50. This is asingle user solution This is the least flexible since the database can not be shared No Consideration of protein secondary structure prediction
- 53. Local ‘GenBank’ withrandom access ‘GenBank’ in Relational format Easy load of NCBI taxonomy data into Local DB Integrated sequence and annotation databases Handy Tool For Bioinformatics Community
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