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1.  PosMed: ranking genes and bioresources based on Semantic Web Association Study 
Nucleic Acids Research  2013;41(Web Server issue):W109-W114.
Positional MEDLINE (PosMed; http://biolod.org/PosMed) is a powerful Semantic Web Association Study engine that ranks biomedical resources such as genes, metabolites, diseases and drugs, based on the statistical significance of associations between user-specified phenotypic keywords and resources connected directly or inferentially through a Semantic Web of biological databases such as MEDLINE, OMIM, pathways, co-expressions, molecular interactions and ontology terms. Since 2005, PosMed has long been used for in silico positional cloning studies to infer candidate disease-responsible genes existing within chromosomal intervals. PosMed is redesigned as a workbench to discover possible functional interpretations for numerous genetic variants found from exome sequencing of human disease samples. We also show that the association search engine enhances the value of mouse bioresources because most knockout mouse resources have no phenotypic annotation, but can be associated inferentially to phenotypes via genes and biomedical documents. For this purpose, we established text-mining rules to the biomedical documents by careful human curation work, and created a huge amount of correct linking between genes and documents. PosMed associates any phenotypic keyword to mouse resources with 20 public databases and four original data sets as of May 2013.
doi:10.1093/nar/gkt474
PMCID: PMC3692089  PMID: 23761449
2.  The RIKEN integrated database of mammals 
Nucleic Acids Research  2010;39(Database issue):D861-D870.
The RIKEN integrated database of mammals (http://scinets.org/db/mammal) is the official undertaking to integrate its mammalian databases produced from multiple large-scale programs that have been promoted by the institute. The database integrates not only RIKEN’s original databases, such as FANTOM, the ENU mutagenesis program, the RIKEN Cerebellar Development Transcriptome Database and the Bioresource Database, but also imported data from public databases, such as Ensembl, MGI and biomedical ontologies. Our integrated database has been implemented on the infrastructure of publication medium for databases, termed SciNetS/SciNeS, or the Scientists’ Networking System, where the data and metadata are structured as a semantic web and are downloadable in various standardized formats. The top-level ontology-based implementation of mammal-related data directly integrates the representative knowledge and individual data records in existing databases to ensure advanced cross-database searches and reduced unevenness of the data management operations. Through the development of this database, we propose a novel methodology for the development of standardized comprehensive management of heterogeneous data sets in multiple databases to improve the sustainability, accessibility, utility and publicity of the data of biomedical information.
doi:10.1093/nar/gkq1078
PMCID: PMC3013680  PMID: 21076152
3.  SDOP-DB: a comparative standardized-protocol database for mouse phenotypic analyses 
Bioinformatics  2010;26(8):1133-1134.
Summary: This article reports the development of SDOP-DB, which can provide definite, detailed and easy comparison of experimental protocols used in mouse phenotypic analyses among institutes or laboratories. Because SDOP-DB is fully compliant with international standards, it can act as a practical foundation for international sharing and integration of mouse phenotypic information.
Availability: SDOP-DB (http://www.brc.riken.jp/lab/bpmp/SDOP/)
Contact: hmasuya@brc.riken.jp
Supplementary information: Supplementary data are available at Bioinformatics online.
doi:10.1093/bioinformatics/btq095
PMCID: PMC2853689  PMID: 20194625
4.  A monogenic dominant mutation in Rom1 generated by N-ethyl-N-nitrosourea mutagenesis causes retinal degeneration in mice 
Molecular Vision  2010;16:378-391.
Purpose
To characterize an N-ethyl-N-nitrosourea-induced dominant mouse mutant, M-1156, that exhibits progressive retinal degeneration and to investigate the pathogenesis of the retinal phenotype in the mutant.
Methods
A positional candidate gene approach was used to identify the causative gene in the M-1156 mutant. Funduscopic examination, light microscopy, transmission electron microscopy, and electroretinography were performed to analyze the M-1156 phenotype. Real-time quantitative PCR, immunohistochemistry, and western blotting were also performed.
Results
Linkage analysis enabled the mutant gene to be mapped to a region of chromosome 19 containing Rom1, which encodes rod outer segment membrane protein 1. Sequence analysis demonstrated that the mutation consisted of a single base T→C substitution at position 1,195 in Rom1 (M96760, National Center for Biotechnology Information [NCBI]) and that the mutant allele was expressed. A putative missense mutation designated Rom1Rgsc1156 that was identified in the M-1156 mutant mouse causes a Trp to Arg substitution at position 182 in the translated protein. Rom1Rgsc1156 heterozygotes were found to have a mottled retina and narrowed arteries in the fundus oculi. Photomicrographs of the retina revealed significant differences among the genotypes in the thickness of the outer nuclear layer and in the length of the outer segments of the photoreceptors. The alterations were more marked in the homozygotes than in the heterozygotes. Electron micrographs showed that the diameters of the discs varied in the heterozygotes and that the discs were more compactly stacked than in the wild type. There were significant differences among the genotypes in the amplitude of the a-wave in single-flash electroretinograms, but there were no significant differences among the photopic electroretinograms. Real-time quantitative PCR showed that there were no significant differences among the genotypes in Rom1 or peripherin/rds (Prph2) mRNA levels relative to the rhodopsin (Rho) mRNA level. Rom1 and Prph2 immunoreactivity were decreased in the retinas of the Rom1Rgsc1156 mutants. Semiquantitative western blot analysis of retinas from 3-week-old Rom1Rgsc1156 mutants demonstrated significant decreases in Rom1, Prph2, and Rho protein levels in all of the genotypes.
Conclusions
The Trp182Arg substitution in Rom1Rgsc1156 mutants causes retinal degeneration. The results suggested that Trp182Arg mutant Rom1 causes a decrease in the levels of wild-type Prph2 and Rom1, which in turn cause a reduction in the level of Prph2 containing tetramers in the disc rim region and ultimately result in unstable, disorganized outer segments and photoreceptor degeneration.
PMCID: PMC2838736  PMID: 20300562
5.  Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project 
Nature biotechnology  2008;26(8):889-896.
The Minimum Information for Biological and Biomedical Investigations (MIBBI) project provides a resource for those exploring the range of extant minimum information checklists and fosters coordinated development of such checklists.
doi:10.1038/nbt.1411
PMCID: PMC2771753  PMID: 18688244
6.  PosMed (Positional Medline): prioritizing genes with an artificial neural network comprising medical documents to accelerate positional cloning 
Nucleic Acids Research  2009;37(Web Server issue):W147-W152.
PosMed (http://omicspace.riken.jp/) prioritizes candidate genes for positional cloning by employing our original database search engine GRASE, which uses an inferential process similar to an artificial neural network comprising documental neurons (or ‘documentrons’) that represent each document contained in databases such as MEDLINE and OMIM. Given a user-specified query, PosMed initially performs a full-text search of each documentron in the first-layer artificial neurons and then calculates the statistical significance of the connections between the hit documentrons and the second-layer artificial neurons representing each gene. When a chromosomal interval(s) is specified, PosMed explores the second-layer and third-layer artificial neurons representing genes within the chromosomal interval by evaluating the combined significance of the connections from the hit documentrons to the genes. PosMed is, therefore, a powerful tool that immediately ranks the candidate genes by connecting phenotypic keywords to the genes through connections representing not only gene–gene interactions but also other biological interactions (e.g. metabolite–gene, mutant mouse–gene, drug–gene, disease–gene and protein–protein interactions) and ortholog data. By utilizing orthologous connections, PosMed facilitates the ranking of human genes based on evidence found in other model species such as mouse. Currently, PosMed, an artificial superbrain that has learned a vast amount of biological knowledge ranging from genomes to phenomes (or ‘omic space’), supports the prioritization of positional candidate genes in humans, mouse, rat and Arabidopsis thaliana.
doi:10.1093/nar/gkp384
PMCID: PMC2703941  PMID: 19468046

Results 1-6 (6)