Journal article
Investigation of protein functions through data-mining on integrated human transcriptome database, H-Invitational database (H-InvDB)
Gene, Vol.364, pp.99-107
2005
Abstract
H-Invitational Database (H-InvDB; http://www.h-invitational.jp/) is a human transcriptome database, containing integrative annotation of 41,118 full-length cDNA clones originated from 21,037 loci. H-InvDB is a product of the H-Invitational project, an international collaboration to systematically and functionally validate human genes by analysis of a unique set of high quality full-length cDNA clones using automatic annotation and human curation under unified criteria. Here, 19,574 proteins encoded by these cDNAs were classified into 11,709 function-known and 7865 function-unknown hypothetical proteins by similarity with protein databases and motif prediction (InterProScan). The proportion of "hypothetical proteins" in H-InvDB was as high as 40.4%. In this study, we thus conducted data-mining in H-InvDB with the aim of assigning advanced functional annotations to those hypothetical proteins. First, by data-mining in the H-InvDB version of GTOP, we identified 337 SCOP domains within 7865 H-Inv hypothetical proteins. Second, by data-mining of predicted subcellular localization by SOSUI and TMHMM in H-InvDB, we found 1032 transmembrane proteins within H-Inv hypothetical proteins. These results clearly demonstrate that structural prediction is effective for functional annotation of proteins with unknown functions. All the data in H-InvDB are shown in two main views, the cDNA view and the Locus view, and five auxiliary databases with web-based viewers; DiseaseInfo Viewer, H-ANGEL, Clustering Viewer, G-integra and TOPO Viewer; the data also are provided as flat files and XML files. The data consists of descriptions of their gene structures, novel alternative splicing isoforms, functional RNAs, functional domains, subcellular localizations, metabolic pathways, predictions of protein 3D structure, mapping of SNPs and microsatellite repeat motifs in relation with orphan diseases, gene expression profiling, and comparisons with mouse full-length cDNAs in the context of molecular evolution. This unique integrative platform for conducting in silico data-mining represents a substantial contribution to resources required for the exploration of human biology and pathology.
Details
- Title
- Investigation of protein functions through data-mining on integrated human transcriptome database, H-Invitational database (H-InvDB)
- Authors/Creators
- C. Yamasaki (Author/Creator) - National Institute of Advanced Industrial Science and TechnologyK.O. Koyanagi (Author/Creator) - Hokkaido UniversityY. Fujii (Author/Creator) - National Institute of Advanced Industrial Science and TechnologyT. Itoh (Author/Creator) - National Institute of Advanced Industrial Science and TechnologyR. Barrero (Author/Creator) - National Institute of GeneticsT. Tamura (Author/Creator) - Japan Biological Informatics ConsortiumY. Yamaguchi-Kabata (Author/Creator) - National Institute of Advanced Industrial Science and TechnologyM. Tanino (Author/Creator) - National Institute of Advanced Industrial Science and TechnologyJ-I Takeda (Author/Creator) - National Institute of Advanced Industrial Science and TechnologyS. Fukuchi (Author/Creator) - National Institute of GeneticsS. Miyazaki (Author/Creator) - Tokyo University of ScienceN. Nomura (Author/Creator) - National Institute of Advanced Industrial Science and TechnologyS. Sugano (Author/Creator) - National Institute of Advanced Industrial Science and TechnologyT. Imanishi (Author/Creator) - National Institute of Advanced Industrial Science and TechnologyT. Gojobori (Author/Creator) - National Institute of Advanced Industrial Science and Technology
- Publication Details
- Gene, Vol.364, pp.99-107
- Publisher
- Elsevier BV
- Identifiers
- 991005543811807891
- Copyright
- © 2005 Elsevier B.V.
- Murdoch Affiliation
- Murdoch University
- Language
- English
- Resource Type
- Journal article
UN Sustainable Development Goals (SDGs)
This output has contributed to the advancement of the following goals:
Source: InCites
Metrics
35 Record Views
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Collaboration types
- Domestic collaboration
- Citation topics
- 1 Clinical & Life Sciences
- 1.54 Molecular & Cell Biology - Genetics
- 1.54.79 Genomic Bioinformatics
- Web Of Science research areas
- Genetics & Heredity
- ESI research areas
- Molecular Biology & Genetics