Difference between revisions of "Textpresso-based automated extraction of concise descriptions"

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==Generating gene sets with and without concise descriptions==
 
  
====Set of genes with a concise description====
 
Query for all genes with a concise description from Postgres:
 
Relevant postgres table names:
 
*con_wbgene: Stores the WBGene ID and gene names
 
*con_desctype: Type of description (relevant for us: Concise_description)
 
*con_desctext: Text of the concise description
 
 
Query for all WBGenes that have a concise description (in con_desctext AND con_desctype):
 
 
SELECT DISTINCT(con_wbgene) FROM con_wbgene WHERE joinkey IN (SELECT joinkey FROM con_desctext WHERE con_desctext IS NOT NULL) AND joinkey IN (SELECT joinkey FROM con_desctype WHERE con_desctype IS NOT NULL) ORDER BY con_wbgene;
 
 
*Number of genes with a concise description (as of 05.07.2014)=6,624
 
 
====Set of genes with no concise description====
 
====Set of genes with no concise description and at least one published paper====
 
 
==Semantic categories in a Concise Description==
 
 
1. Molecular identity <br \>
 
2. Orthology/Similarity <br \>
 
3. Mutant Phenotypes <br \>
 
4. Processes <br \>
 
5. Pathways <br \>
 
6. Genetic Interaction<br \>
 
7. Physical Interaction <br \>
 
8. Molecular Function <br \>
 
9. Tissue expression  (may include life-stage) <br \>
 
10. Sub-cellular localization  (may include life-stage) <br \>
 
 
==Template for a Concise Description==
 
'''Molecular identity'''
 
<Gene> encodes .....;
 
'''Orthology/Similarity'''
 
<Gene> is (orthologous, similar) to .....;
 
'''Process/Pathway'''
 
<Gene> is (required, functions, regulates, is involved in, is part of) ....., as mutants of <gene> exhibit <phenotypes>;
 
'''Genetic interaction with respect to Process or Pathway'''
 
<Gene> interacts genetically with <gene1, gene2> ..... in <Process, Pathway>;
 
'''Physical interaction'''
 
<Protein> physically interacts with (protein, DNA, RNA) .....;
 
'''Molecular Function'''
 
<Protein> has ..... activity in (in vitro, in vivo) assays;
 
'''Tissue Expression'''
 
<Gene/Protein> is expressed in ..... and expression in ..... is (positively, negatively)
 
regulated by <Gene/Protein>.....;
 
'''Sub-cellular localization'''
 
<Protein> is localized to <cellular component> and expression in <cellular component>
 
is <positively, negatively> regulated by .....
 
 
Note: Not all descriptions may follow the exact order or choice of words.
 
 
==Data mining (mining data from Postgres and/or Acedb) for the semantic categories==
 
1. Molecular identity and Orthology data (Homology, Orthology and Paralog data)
 
*Non-caltech data, curated at Hinxton
 
*Ace tags: ?Gene Ortholog_other, Paralog
 
*Contact: Michael Paulini
 
 
3. Processes
 
*Caltech data
 
*2 sources: GO data and Topic data
 
*Sources for GO data: GO OA and GO file from Protein2GO
 
*GO OA, Postgres (PG) table name:
 
*Easier to use the gene_association file:ftp://ftp.wormbase.org/pub/wormbase/releases/WS243/ONTOLOGY/
 
*File name:gene_association.WS243.wb.c_elegans
 
*Rows with a 'P' in column 9 indicates GO Biological Process associated with a gene.
 
*Contact Person: Kimberly, Ranjana
 
 
*Topic OA:
 
*OA field:Gene, PG table name:pro_wbgene
 
*OA field:WBPaper, PG table name:pro_paper
 
*Contact Person: Karen
 
 
4. Pathway
 
(No database source for now?)
 
 
 
5. Mutant Phenotypes
 
*Caltech data
 
*Phenotype OA, PG table name:(Phenotypes are added to variation and not genes)
 
*Acedb tag: Under ?Gene, Reference_allele ?Variation and Allele ?Variation and Under ?Variation Phenotype
 
*Might be easier to use the phenotype_association file:ftp://ftp.wormbase.org/pub/wormbase/releases/WS243/ONTOLOGY/
 
*File name:phenotype_association.WS243.wb
 
 
*Contact Person: Karen
 
 
6. Genetic Interaction and 7. Physical Interaction
 
*Caltech data
 
*Source: Interaction OA and tables
 
*"Field Name" = Postgres Table:
 
*"Paper" = int_paper
 
*"Interaction Type" = int_type
 
*"Bait overlapping gene" = int_genebait
 
*"Target overlapping gene" = int_genetarget
 
*"Non-directional Gene(s)" = int_genenondir
 
*"Effector Gene(s)" = int_geneone
 
*"Affected Gene(s)" = int_genetwo
 
 
Example statements:
 
 
If int_type = "Physical"
 
 
<int_genebait> interacts physically with <int_genetarget> (and vice versa)
 
 
 
If int_type = "Genetic - Synthetic ( Synthetic )"
 
 
<int_genenondir> interacts with <other int_genenondir(s)> in a synthetic
 
genetic interaction
 
 
 
If int_type = "Genetic - Suppression ( Suppression )"
 
 
<int_geneone> genetically suppresses <int_genetwo>
 
 
 
8. Molecular Function
 
*Caltech data: GO Molecular Function
 
*File for GO data (for protein-encoding genes only):
 
*GO OA, PG table name:
 
*Might be easier to use the gene_association.WSXXX.c_elegans file:Index of ftp://ftp.wormbase.org/pub/wormbase/releases/WS243/ONTOLOGY/
 
*Rows with a 'F' in column 9 indicates GO molecular function associated with a gene.
 
*Contact Person: Kimberly, Ranjana
 
 
 
9. Tissue expression and life stage
 
*Caltech data
 
*Expression OA (exprpat), PG table names:
 
*tables are:
 
*exp_anatomy for anatomy terms
 
*exp_goid for subcell localization
 
*exp_lifestage for life stage
 
*exp_paper for paper
 
*exp_gene for gene
 
*Contact Person: Daniela
 
 
 
10. Sub-cellular localization
 
*Caltech data
 
*Source: GO cellular component
 
*Source 1-ftp://ftp.wormbase.org/pub/wormbase/releases/WS243/ONTOLOGY/
 
*File name:gene_association.WS243.wb.c_elegans
 
 
 
 
 
 
 
====Publications related to Text-mining methods====
 
*Automatically generating gene summaries from biomedical literature.
 
 
Ling X, Jiang J, He X, Mei Q, Zhai C, Schatz B.
 
 
Pac Symp Biocomput. 2006:40-51.
 
 
PMID:17094226
 
 
*Generating gene summaries from biomedical literature: A study of semi-structured summarization
 
 
Xu Ling *, Jing Jiang, Xin He, Qiaozhu Mei, Chengxiang Zhai, Bruce Schatz
 
 
Information Processing and Management 43 (2007) 1777–1791
 
 
 
Back To [[Concise Descriptions]]
 

Latest revision as of 23:01, 10 September 2014