PosMed-plus: an intelligent search engine that inferentially integrates cross-species information resources for molecular breeding of plants.

Molecular breeding of crops is an efficient way to upgrade plant functions useful to mankind. A key step is forward genetics or positional cloning to identify the genes that confer useful functions. In order to accelerate the whole research process, we have developed an integrated database system powered by an intelligent data-retrieval engine termed PosMed-plus (Positional Medline for plant upgrading science), allowing us to prioritize highly promising candidate genes in a given chromosomal interval(s) of Arabidopsis thaliana and rice, Oryza sativa.

PosMed (Positional Medline): prioritizing genes with an artificial neural network comprising medical documents to accelerate positional cloning.

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.

Phenosite: a web database integrating the mouse phenotyping platform and the experimental procedures in mice.

Recently, a number of collaborative large-scale mouse mutagenesis programs have been launched. These programs aim for a better understanding of the roles of all individual coding genes and the biological systems in which these genes participate. In international efforts to share phenotypic data among facilities/institutes, it is desirable to integrate information obtained from different phenotypic platforms reliably.

OmicBrowse: a browser of multidimensional omics annotations.

Unlabelled: OmicBrowse is a browser to explore multiple datasets coordinated in the multidimensional omic space integrating omics knowledge ranging from genomes to phenomes and connecting evolutional correspondences among multiple species. OmicBrowse integrates multiple data servers into a single omic space through secure peer-to-peer server communications, so that a user can easily obtain an integrated view of distributed data servers, e.g.

A flexible representation of omic knowledge for thorough analysis of microarray data.

Background: In order to understand microarray data reasonably in the context of other existing biological knowledge, it is necessary to conduct a thorough examination of the data utilizing every aspect of available omic knowledge libraries. So far, a number of bioinformatics tools have been developed. However, each of them is restricted to deal with one type of omic knowledge, e.

In silico phenotypic screening method of mutants based on statistical modeling of genetically mixed samples.

In comprehensive functional genomics projects, systematic analysis of phenotypes is vital. However, conventional phenotypic screening is done mainly by imprecise visual observation of qualitative traits, and, therefore, in silico screening techniques for quantitative traits are required. In this report, we propose in silico phenotypic screening method that utilizes a Gaussian mixture model for the trait distribution in the offspring of a mutagenized line and the likelihood ratio test between the estimated Gaussian mixture model and the wild-type single Gaussian model.

Three-dimensional definition of leaf morphological traits of Arabidopsis in silico phenotypic analysis.

The detection of phenotypic alterations of mutants and variants is one of the bottlenecks that hinder systematic gene functional studies of the model plant Arabidopsis. In an earlier study, we have addressed this problem by proposing a novel methodology for phenome analysis based on in silico analysis of polygon models that are acquired by 3-dimensional (3D) measurement and which precisely reconstruct the actual plant shape. However, 3D quantitative descriptions of morphological traits are rare, whereas conventional 2D descriptions have already been studied but may lack the necessary precision.

TraitMap: an XML-based genetic-map database combining multigenic loci and biomolecular networks.

Motivation: Most ordinary traits are well described by multiple measurable parameters. Thus, in the course of elucidating the genes responsible for a given trait, it is necessary to conduct and integrate the genetic mapping of each parameter. However, the integration of multiple mapping results from different publications is prevented by the fact that they are conventionally published and accumulated in printed forms or graphics which are difficult for computers to reuse for further analyses.

Automatic quantification of morphological traits via three-dimensional measurement of Arabidopsis.

Many mutants have been isolated from the model plant Arabidopsis thaliana, and recent important genetic resources, such as T-DNA knockout lines, facilitate the speed of identifying new mutants. However, present phenotypic analysis of mutant screens depends mainly on qualitative descriptions after visual observation of morphological traits. We propose a novel method of phenotypic analysis based on precise three-dimensional (3D) measurement by a laser range finder (LRF) and automatic data processing.