G-language Genome Analysis Environment Research Articles

GEMBASSY: an EMBOSS associated software package for comprehensive genome analyses

The popular European Molecular Biology Open Software Suite (EMBOSS) currently contains over 400 tools used in various bioinformatics researches, equipped with sophisticated development frameworks for interoperability and tool discoverability as well as rich documentations and various user interfaces. In order to further strengthen EMBOSS in the fields of genomics, we here present a novel EMBOSS associated software (EMBASSY) package named GEMBASSY, which adds more than 50 analysis tools from the G-language Genome Analysis Environment and its Representational State Transfer (REST) and SOAP web services. GEMBASSY basically contains wrapper programs of G-language REST/SOAP web services to provide intuitive and easy access to various annotations within complete genome flatfiles, as well as tools for analyzing nucleic composition, calculating codon usage, and visualizing genomic information. For example, analysis methods such as for calculating distance between sequences by genomic signatures and for predicting gene expression levels from codon usage bias are effective in the interpretation of meta-genomic and meta-transcriptomic data. GEMBASSY tools can be used seamlessly with other EMBOSS tools and UNIX command line tools. The source code written in C is available from GitHub (https://github.com/celery-kotone/GEMBASSY/) and the distribution package is freely available from the GEMBASSY web site (http://www.g-language.org/gembassy/).

G-language genome analysis environment with REST and SOAP web service interfaces

G-language genome analysis environment (G-language GAE) contains more than 100 programs that focus on the analysis of bacterial genomes, including programs for the identification of binding sites by means of information theory, analysis of nucleotide composition bias and the distribution of particular oligonucleotides, calculation of codon bias and prediction of expression levels, and visualization of genomic information. We have provided a collection of web services for these programs by utilizing REST and SOAP technologies. The REST interface, available at http://rest.g-language.org/, provides access to all 145 functions of the G-language GAE. These functions can be accessed from other online resources. All analysis functions are represented by unique universal resource identifiers. Users can access the functions directly via the corresponding universe resource locators (URLs), and biological web sites can readily embed the functions by simply linking to these URLs. The SOAP services, available at http://www.g-language.org/wiki/soap/, provide language-independent programmatic access to 77 analysis programs. The SOAP service Web Services Definition Language file can be readily loaded into graphical clients such as the Taverna workbench to integrate the programs with other services and workflows.

A web server for interactive and zoomable Chaos Game Representation images

Chaos Game Representation (CGR) is a generalized scale-independent Markov transition table, which is useful for the visualization and comparative study of genomic signature, or for the study of characteristic sequence motifs. However, in order to fully utilize the scale-independent properties of CGR, it should be accessible through scale-independent user interface instead of static images. Here we describe a web server and Perl library for generating zoomable CGR images utilizing Google Maps API, which is also easily searchable for specific motifs. The web server is freely accessible at , and the Perl library as well as the source code is distributed with the G-language Genome Analysis Environment under GNU General Public License.

Restauro-G: A Rapid Genome Re-Annotation System for Comparative Genomics

Annotations of complete genome sequences submitted directly from sequencing projects are diverse in terms of annotation strategies and update frequencies. These inconsistencies make comparative studies difficult. To allow rapid data preparation of a large number of complete genomes, automation and speed are important for genome re-annotation. Here we introduce an open-source rapid genome re-annotation software system, Restauro-G, specialized for bacterial genomes. Restauro-G re-annotates a genome by similarity searches utilizing the BLAST-Like Alignment Tool, referring to protein databases such as UniProt KB, NCBI nr, NCBI COGs, Pfam, and PSORTb. Re-annotation by Restauro-G achieved over 98% accuracy for most bacterial chromosomes in comparison with the original manually curated annotation of EMBL releases. Restauro-G was developed in the generic bioinformatics workbench G-language Genome Analysis Environment and is distributed at http://restauro-g.iab.keio.ac.jp/ under the GNU General Public License.

G-language System as a platform for large-scale analysis of high-throughput omics data

The advent of high-throughput measurement technologies has resulted in the rapid accumulation of “omics” information including genome, transcriptome, proteome, and metabolome data. This increase in data acquisition has lead to a demand for an efficient computational platform for in silico analysis. The G-language software suite provides a comprehensive workbench for large-scale omics research and systems biology. The suite includes a bioinformatics research framework G-language Genome Analysis Environment, which contains a Gene Prediction Accuracy Classification benchmarking tool for the quantification of the sensitivity of genome informatics analysis methods to genome annotation completeness. Omics data processed in this environment can be visualized with KEGG-based pathway mapping web service, and Genome-based Modeling System enables automatic prototyping of metabolic pathway models from the genome. The software suite covers various domains of omics, with the goal of integrating all of these data for research into systems biology.

G-language Genome Analysis Environment: a workbench for nucleotide sequence data mining.

G-language Genome Analysis Environment (G-language GAE) is an open source generic software package aimed for higher efficiency in bioinformatics analysis. G-language GAE has an interface as a set of Perl libraries for software development, and a graphical user interface for easy manipulation. Both Windows and Linux versions are available. From http://www.g-language.org/ under GNU General Public License. CD-ROMs are distributed freely in major conferences.

Microarray Visualization System on the G-Language GAE

In this work, we have developed the Microarray Visualization System over the generic bioinformatics workbench G-language Genome Analysis Environment (G-language GAE) [5] which automatically maps the expression data driven from multiple experimental conditions onto the KEGG database [2], subsequently displaying in HTML/SWF format the corresponding enzymes and its metabolic pathway. Aside from other G-language GAE applications using inspire technology (The E-CELL ECD VIEWER, Bacteria Analysis System over FLASH), the Microarray Visualization System uses SWFoverMing [3, 4, 5] as its core kernel. By requiring no bypasses through Macromedia Flash the Microarray Visualization System was developed as a pure open source application (GNU General Public License) by making full use of Perl and SWFoverMing to act as a sustainable and generic application.

Automatic Generation of Cell-Wide Pathway Model from Complete Genome

Knowledge in molecular biology is rapidly accumulating in the fields of genome, transcriptome, proteome, and metabolome, demanding for a systems biology approach in order to view the dynamic behavior of a cell as a complex system. However, simulation is a challenging task especially where large-scale modeling is required due to the necessity for vast amount of accurate parameters. E-Cell project [2] estimated the necessary cost for modeling the whole cell of Escherichia coli to be at least 1800 man month, from the experience in modeling an in silico mitochondria. Therefore a large scale modeling of cell in silico demands for a novel high-throughput approach. If successfully integrated, availability of large amount of genome sequence, transcripts and expression data, enzyme reaction data, metabolic pathway maps, and the data of metabolites in cells will create a strong base for a qualitative cell model. The Genome-based E-cell Modeling System (GEM System) developed upon the generic bioinformatics workbench G-language Genome Analysis Environment [1] realizes a fully automatic conversion of genome sequence data into a qualitative in silico cell model, linking information from major public databas such as GenBank, EMBL, SWISS-PROT, KEGG, ARM, Brend, and WIT.

G-Language Genome Analysis Environment Version 2

G-language Project of Institute for Advanced Biosciences aims to introduce higher efficiency in genome analysis by: 1. Constructing an integrated environment for the development of analysis software. 2. Systematically accumulating existing analysis software, methodologies for analysis and their results. 3. Constructing generic analysis packages that allow users to avoid redundancy in the process of analysis. We are currently developing G-language Genome Analysis Environment (G-language GAE)[1] version 2 which will be publicly released in Q2 of 2004. G-language GAE version 2 aims to provide a more flexible and sophisticated workbench for different layers of life sciences, including genome, transcriptome, proteome, metabolome, and systeome. Software download is available at http://www. g-language.org/.

Development of Chi Sequence Analysis System on the G-Language Genome Analysis Environment

The Chi sequence in Escherichia coli is a GT-rich octamer (5’ GCTGGTGG 3’) that acts as a signal sequence for a recombinase, RecBCD (Exonuclease V) [2]. Homologous recombination promoted by cis-acting sequence element is a widely conserved mechanism in eubacteria, and although the signal sequences differ among species, Chi analogues are identified in certain species whose complete genomes are available. As more and more complete genomes of bacteria become available at an increasing rate, it has been needed to systemize a set of analyses for higher efficiency to cope with the increasing amount of data. We have developed the Chi Sequence Analysis System on the G-language Genome Analysis Environment to analyze Chi sequences and other oligomers efficiently independent of the formats of genome databases and regardless of the types of oligomers and species. G-language Genome Analysis Environment (G-language GAE) is a generic platform for the bioinformatics analysis and software development [1]. Analysis programs can be systemized into a cascade of analyses on G-language GAE with multiple user interfaces, therefore once a set of analyses is systemized, the set of analyses can be applied to different genomes simply by a few mouse clicks from the graphical user interface.

Development of Comparative Genome Analysis System (COMGA) on the G-Language Genome Analysis Environment

Detection and analysis of the preservation and mutation in nucleotide sequences are indispensable processes to solve the evolutionary mechanism and characteristics. Comparative genome analysis is also very effective for phylogenetic analyses, but the vast amount of information required in the process demands for a higher efficiency. Therefore, computational analysis is necessary for such purposes. G-language Genome Analysis Environment (G-language GAE) is a generic analysis workbench for genome analysis [1]. We have been developing a system called COMGA for easier comparison of two or more genome databases. By integrating COMGA on the G-language GAE, all of its tools are accessible as Perl functions with multiple front-end interfaces. COMGA provides graphical and interactive output for the comparative genome analysis. Intuitive access is provided to analyze and refer to the difference of not only each genome but also the difference of each gene within the genomes.

Development of the Bacteria Analysis System on G-Language Genome Analysis Environment

Development of the Bacteria Analysis System on G-Language Genome Analysis Environment