Biomedical subjects

Masumi Itoh

Publications and source records attributed to Masumi Itoh.

7 recordsLinked to original sources

PubMed2006

EGassembler: online bioinformatics service for large-scale processing, clustering and assembling ESTs and genomic DNA fragments.

Expressed sequence tag (EST) sequencing has proven to be an economically feasible alternative for gene discovery in species lacking a draft genome sequence. Ongoing large-scale EST sequencing projects feel the need for bioinformatics tools to facilitate uniform EST handling. This brings about a renewed importance for a universal tool for processing and functional annotation of large sets of ESTs. EGassembler (http://egassembler.hgc.jp/) is a web server, which provides an automated as well as a user-customized analysis tool for cleaning, repeat masking, vector trimming, organelle masking, clustering and assembling of ESTs and genomic fragments. The web server is publicly available and provides the community a unique all-in-one online application web service for large-scale ESTs and genomic DNA clustering and assembling. Running on a Sun Fire 15K supercomputer, a significantly large volume of data can be processed in a short period of time. The results can be used to functionally annotate genes, to facilitate splice alignment analysis, to link the transcripts to genetic and physical maps, design microarray chips, to perform transcriptome analysis and to map to KEGG metabolic pathways. The service provides an excellent bioinformatics tool to research groups in wet-lab as well as an all-in-one-tool for sequence handling to bioinformatics researchers.

Computational Biology↗

PubMed2006

From genomics to chemical genomics: new developments in KEGG.

The increasing amount of genomic and molecular information is the basis for understanding higher-order biological systems, such as the cell and the organism, and their interactions with the environment, as well as for medical, industrial and other practical applications. The KEGG resource (http://www.genome.jp/kegg/) provides a reference knowledge base for linking genomes to biological systems, categorized as building blocks in the genomic space (KEGG GENES) and the chemical space (KEGG LIGAND), and wiring diagrams of interaction networks and reaction networks (KEGG PATHWAY). A fourth component, KEGG BRITE, has been formally added to the KEGG suite of databases. This reflects our attempt to computerize functional interpretations as part of the pathway reconstruction process based on the hierarchically structured knowledge about the genomic, chemical and network spaces. In accordance with the new chemical genomics initiatives, the scope of KEGG LIGAND has been significantly expanded to cover both endogenous and exogenous molecules. Specifically, RPAIR contains curated chemical structure transformation patterns extracted from known enzymatic reactions, which would enable analysis of genome-environment interactions, such as the prediction of new reactions and new enzyme genes that would degrade new environmental compounds. Additionally, drug information is now stored separately and linked to new KEGG DRUG structure maps.

Biotransformation↗

PubMed2006

Extracting sequence motifs and the phylogenetic features of SNARE-dependent membrane traffic.

The SNARE proteins are required for membrane fusion during intracellular vesicular transport and for its specificity. Only the unique combination of SNARE proteins (cognates) can be bound and can lead to membrane fusion, although the characteristics of the possible specificity of the binding combinations encoded in the SNARE sequences have not yet been determined. We discovered by whole genome sequence analysis that sequence motifs (conserved sequences) in the SNARE motif domains for each protein group correspond to localization sites or transport pathways. We claim that these motifs reflect the specificity of the binding combinations of SNARE motif domains. Using these motifs, we could classify SNARE proteins from 48 organisms into their localization sites or transport pathways. The classification result shows that more than 10 SNARE subgroups are kingdom specific and that the SNARE paralogs involved in the plasma membrane-related transport pathways have developed greater variations in higher animals and higher plants than those involved in the endoplasmic reticulum-related transport pathways throughout eukaryotic evolution.

Amino Acid Motifs↗

PubMed2004

Fast and accurate database homology search using upper bounds of local alignment scores.

MOTIVATION: It is widely recognized that homology search and ortholog clustering are very useful for analyzing biological sequences. However, recent growth of sequence database size makes homolog detection difficult, and rapid and accurate methods are required. RESULTS: We present a novel method for fast and accurate homology detection, assuming that the Smith-Waterman (SW) scores between all similar sequence pairs in a target database are computed and stored. In this method, SW alignment is computed only if the upper bound, which is derived from our novel inequality, is higher than the given threshold. In contrast to other methods such as FASTA and BLAST, this method is guaranteed to find all sequences whose scores against the query are higher than the specified threshold. Results of computational experiments suggest that the method is dozens of times faster than SSEARCH if genome sequence data of closely related species are available.

Algorithms↗

PubMed2004

Using protein motif combinations to update KEGG pathway maps and orthologue tables.

We have studied the projection of protein family data onto single bacterial translated genome as a solution to visualise relationships between families restricted to bacterial sequences. Any member of any type of family as defined in the Pfam database (domains, signatures, etc.) is considered as a protein module. Our first goal is to discover rules correlating the occurrence of modules with biochemical properties. To achieve this goal we have developed a platform to quantify information found in protein databases and to support the analysis of the nature of modules, their position and corresponding frequencies of occurrence (in isolation or in combination) in association with pathway knowledge as found in KEGG. This paper focuses on two pathways: the two-component system and the aminophosphonate metabolism, that are partially but not completely documented. Proteins involved in those pathways were listed separately in each organism to analyse module composition and rules constraining pathway interactions were identified. It is shown how these results can be used to update KEGG pathways and orthologue tables.

Animals↗

PubMed2004

Clustering of database sequences for fast homology search using upper bounds on alignment score.

Homology data are among the most important information used to predict the functions of unknown proteins and thus fast and accurate methods are needed. In this paper, we propose a new approach for fast and accurate homology search using pre-computed all-against-all similarity scores in a target database. We previously developed a method for derivation of an upper bound of the Smith-Waterman score (SW-score) between a query and a homolog candidate sequence using the SW-score between the candidate and a sequence similar to the query. In this paper, by using this upper bound, we first cluster the sequences in the target database so that upper bounds of SW-scores for all the members in the clusters are less than a given value and select representative sequences for respective clusters. Then, the query sequence is searched against the representative sequences and the upper bounds of SW-scores for respective clusters are estimated. Only if the upper bound is higher than a given threshold, SW-alignments are computed for all the sequences in the cluster. We performed computational experiments to test efficiency of the proposed method for the KEGG/GENES database using the KEGG/SSDB. The results suggest that our method is efficient for redundant databases that include multiple closely related species.

Algorithms↗

PubMed2002

Extraction of organism groups from phylogenetic profiles using independent component analysis.

In recent years, the analysis of orthologous genes based on phylogenetic profiles has received popularity in bioinfomatics. We propose a new method to extract organism groups and their hierarchy from phylogenetic profiles using the independent component analysis (ICA). The method involves first finding independent axes in the projected space from the multivariate data matrix representing phylogenetic profiles for a number of orthologous genes. Then the extracted axes are correlated with major organism groups, according to the extent of affiliation of axes scores for all the genes to specific organisms. The ICA was applied to the phylogenetic profiles created for 2,875 orthologs in 77 organisms by using the KEGG/GENES database. The 9 extracted components out of 18 predefined components well represented the organism groups as categorized in KEGG. Furthermore, we performed the cluster analysis and obtained the hierarchy of organism groups.

Animals↗