BIRDQL

BIRDQL Biological Query Language

BIRDQL in few words

The heterogeneous data integrated in BIRD System are represented by several relational tables. The exploitation of these data by SQL queries is not obvious except for developers or computer scientist experts.

Building queries with SQL in this context is not easy with because that requires to use joins (terme technique) to select data in multiple tables. This complexity must be hidden by HTML forms but a lot of queries can not be setup with HTML forms.

We proposes own query language (BIRDQL), there is new standard biological query language allowing the biologist or clinician to create data retrieval protocols without exhaustive knowledge of the data sources and their architecture. BIRD System is driven with a high level query engine: BIRDQL, which makes it possible for biologists to express easily queries and to extract knowledge by classical constraints and scientific functions (StructuralDistance,SequencePattern,AssociationRule...).

BIRDQL in not a mathematically complete language but indeed an idiom adpated to the GUI, human readable enough to be modified by hand.

BIRDQL Grammar

ID <list of id/ac/query_id > DB <bank names>

WH Field[1] Contains (kw1 & kw2) | kw_n

WH PATTERN <function SequencePattern() >

WH PATTERN <function DiagonalMolecule()>

WH PATTERN <function InteractionProtein()>

WH PATTERN <function AssociationRule()>

FD <Field[2] out>

LM <n>

FM Fasta/Flat/Xml/CSV/Simple/Object/OID

BIRDQL example

Data can also be selected with Two other examples below also show how to use the BIRD-QL syntax.

Example 1: simple query, search and fasta format generation

ID * DB UNIPROT

WH DE contains "synthetase" & "tyrosyl"

WH OX contains 382

FD AC, ID,DE,OX,SQ

FM FASTA

Result

>Q92PK5 | SYY_RHIME | Tyrosyl-tRNA synthetase (EC 6.1.1.1) (Tyrosine--tRNA ligase) (TyrRS). | 382 MSEFKSDFLHTLSERGFIHQTSDDAGLDQLFRTETVTAYIGFDPTAASLHAGGLIQIMMLHWLQATGHRPISLMGGGTGMVGDPSFKDEARQLMTPETI...

Example 2: complex query

ID * DB GENBANK, REFSEQ

WH OC Contains "Eukaryote"

WH DR Contains "GO"

WH GENE contains "GF100027"

FM FASTA

The query above allow to search in Genbank and RefSeq, the Eucaryotic sequences containing the GF100027 gene with a cross reference in GeneOntology.

Example 2: complex query

ID * DB GENBANK, REFSEQ

WH OC Contains "Eukaryote"

WH DR Contains "GO"

WH GENE contains "GF100027"

FM FASTA

The query above allow to search in Genbank and RefSeq, the Eucaryotic sequences containing the GF100027 gene with a cross reference in GeneOntology.

Example 3: mining in EST

ID * DB GBEST

WH TISSUE_TYPE contains "retina"

WH DEV_STAGE contains "adult"

LM 100

FD AC,DE,OX,OC,tissue_type,dev_stage,chr

FM FLAT

Example 4: Mining in EST

ID CJ133635,CJ133593,CJ133659 DB GBEST

WH DE contains "AMINOTRANSFERASE"

WH OC contains "Eukaryota" & not "Metazoa"

WH TISSUE_TYPE contains "retina"

FD AC,DE,OX,OC,tissue_type,dev_stage,chr

FM FLAT

Example 5: Mining in EST

ID * DB GBEST

WH TISSUE_TYPE contains "colon"

WH DEV_STAGE contains "adult"

LM 100

FD AC,DE,OX,OC,tissue_type,dev_stage,chr,os

FM FLAT

Example 6: Mining In PDB

ID * DB PDB

WH DE contains "ERYTHRINA CORALLODENDRON LECTIN IN COMPLEX"

WH OS contains "ERYTHRINA CORALLODENDRON"

WH RESO contains 1.90

LM 10

FM FASTA

//

ID * DB PDB

WH CL contains "METAL BINDING PROTEIN"

WH DE contains "LACTOFERRIN"

WH FUNCTION Diagnonal3D()>125

FUZZY 100

LM 100

FM FASTA

//

ID * DB PDB WH CL contains "METAL BINDING PROTEIN"

WH DE contains "LACTOFERRIN"

WH FUNCTION Diagnonal3D()>125

FUZZY 100

LM 100

FM SIMPLE

//

ID * DB PDB

WH CL contains "METAL BINDING PROTEIN"

WH DE contains "LACTOFERRIN"

WH FUNCTION Diagnonal3D()>125

LM 10

FM FLAT

//

ID * DB PDB

WH CL contains "METAL BINDING PROTEIN"

WH DE contains "LACTOFERRIN"

WH FUNCTION Diagnonal3D()>125

FD GET_COUNT

FM FLAT

Example 7: rmining in EVI Genoret Database

ID * DB EVImm

WH text CONTAINS "retina"

FD GET_COUNT

FM CSV

//

ID * DB EVImm

WH text CONTAINS "retina"

LM 10

FD NOM,VALIDEPROT

FM CSV

//

ID * DB EVImm

WH text CONTAINS "retina"

LM 10

FD NOM,VALIDEPROT

FM FLAT

//

ID * DB EVImm

WH text CONTAINS "retina" & "chr6:127091327-127116667"

LM 10

FM XML

Example 8: running SQL Native (authorized user)

ID * DB STRING

WH SQLNATIVE select * from items.proteins

Limit 100

FM CSV

Example 9: SAGE Data (or GEO) (authorized user)

ID * DB GEO

WH SQLNATIVE select key_fk,tag,count from GEOSAGE.entry where tag='GTGAAACCCC'

LM 500

FM CSV

==> results

GSM1|GTGAAACCCC|63

GSM2|GTGAAACCCC|76

GSM571|GTGAAACCCC|13

GSM572|GTGAAACCCC|395

GSM573|GTGAAACCCC|359

GSM574|GTGAAACCCC|286

GSM668|GTGAAACCCC|132

GSM669|GTGAAACCCC|129

GSM670|GTGAAACCCC|112

//

ID * DB GEO

WH SQLNATIVE select e.key_fk,e.tag,e.count from GEOSAGE.entry as e, GEOSAGE.header as h where (h.sample_id=e.key_fk and tag='GTGAAACCCC') and h.platform_id='GPL4' and count between 1 and 3

LM 1000

FM CSV

Results

GSM135388|GTGAAACCCC|1|GPL4

//

ID * DB GEO

WH SQLNATIVE select key_fk,tag,count from GEOSAGE.entry where tag='GTGAAACCCC' and count between 1 and 3

LM 1000

FM CSV

Example 10: Association rules (authorized user)

ID * DB protein_interaction

WH PATTERN AssociationPattern(Right(protA,ProtB,ProtC),Left(ProtK),sup=30,conf=90))

FD ID,Rules

FM FLAT