RT Journal
A1 Nagashima, Takeshi
A1 Silva, Diego G.
A1 Petrovsky, Nikolai
A1 Socha, Luis A.
A1 Suzuki, Harukazu
A1 Saito, Rintaro
A1 Kasukawa, Takeya
A1 Kurochkin, Igor V.
A1 Konagaya, Akihiko
A1 Schönbach, Christian
T1 Inferring Higher Functional Information for RIKEN Mouse Full-Length cDNA Clones With FACTS
JF Genome Research 
JO Genome Research 
YR 2003 
FD June 01 
VO 13 
IS 6b 
SP 1520 
OP 1533 
DO 10.1101/gr.1019903 
UL http://genome.cshlp.org/content/13/6b/1520.abstract 
AB FACTS (Functional Association/Annotation of cDNA Clones from Text/Sequence  Sources) is a semiautomated knowledge discovery and annotation system that  integrates molecular function information derived from sequence analysis  results (sequence inferred) with functional information extracted from text.  Text-inferred information was extracted from keyword-based retrievals of  MEDLINE abstracts and by matching of gene or protein names to OMIM, BIND, and  DIP database entries. Using FACTS, we found that 47.5% of the 60,770 RIKEN  mouse cDNA FANTOM2 clone annotations were informative for text searches.  MEDLINE queries yielded molecular interaction-containing sentences for 23.1%  of the clones. When disease MeSH and GO terms were matched with retrieved  abstracts, 22.7% of clones were associated with potential diseases, and 32.5%  with GO identifiers. A significant number (23.5%) of disease MeSH-associated  clones were also found to have a hereditary disease association (OMIM  Morbidmap). Inferred neoplastic and nervous system disease represented 49.6%  and 36.0% of disease MeSH-associated clones, respectively. A comparison of  sequence-based GO assignments with informative text-based GO assignments  revealed that for 78.2% of clones, identical GO assignments were provided for  that clone by either method, whereas for 21.8% of clones, the assignments  differed. In contrast, for OMIM assignments, only 28.5% of clones had  identical sequence-based and text-based OMIM assignments. Sequence, sentence,  and term-based functional associations are included in the FACTS database  (http://facts.gsc.riken.go.jp/),  which permits results to be annotated and explored through web-accessible  keyword and sequence search interfaces. The FACTS database will be a critical  tool for investigating the functional complexity of the mouse transcriptome,  cDNA-inferred interactome (molecular interactions), and pathome  (pathologies).