title: Inferring higher functional information for RIKEN mouse full-length cDNA clones with FACTS.
abstract: 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).
authors.affiliation: Biomedical Knowledge Discovery Team, Bioinformatics Group, RIKEN Genomic Sciences Center (GSC), Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan.
authors.forename: Takeshi
authors.initials: T
authors.lastname: Nagashima
authors.forename: Diego G
authors.initials: DG
authors.lastname: Silva
authors.forename: Nikolai
authors.initials: N
authors.lastname: Petrovsky
authors.forename: Luis A
authors.initials: LA
authors.lastname: Socha
authors.forename: Harukazu
authors.initials: H
authors.lastname: Suzuki
authors.forename: Rintaro
authors.initials: R
authors.lastname: Saito
authors.forename: Takeya
authors.initials: T
authors.lastname: Kasukawa
authors.forename: Igor V
authors.initials: IV
authors.lastname: Kurochkin
authors.forename: Akihiko
authors.initials: A
authors.lastname: Konagaya
authors.forename: Christian
authors.initials: C
authors.lastname: Schönbach
mesh_terms: D000818:Animals; D018076:DNA, Complementary / Q000235:genetics / Q000502:physiology*; D030541:Databases, Genetic / Q000639:trends*; D030562:Databases, Protein / Q000639:trends; D019451:Information Management / Q000379:methods* / Q000639:trends*; D016247:Information Storage and Retrieval / Q000379:methods / Q000639:trends; D016239:MEDLINE / Q000639:trends; D051379:Mice; D025941:Protein Interaction Mapping / Q000379:methods / Q000639:trends; D012984:Software / Q000639:trends*
chemical_list: D018076:DNA, Complementary