Inferring higher functional information for RIKEN mouse full-length cDNA Clones with FACTS

Takeshi Nagashima, Diego G. Silva, Nikolai Petrovsky, Luis A. Socha, Harukazu Suzuki, Rintaro Saito, Takeya Kasukawa, Igor V. Kurochkin, Akihiko Konagaya, Christian Schönbach

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)


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 (, 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).

Original languageEnglish
Pages (from-to)1520-1533
Number of pages14
JournalGenome Research
Issue number6 B
Publication statusPublished - 1 Jun 2003
Externally publishedYes


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