[show abstract][hide abstract] ABSTRACT: Sentra (http://compbio.mcs.anl.gov/sentra), a database of signal transduction proteins encoded in completely sequenced prokaryotic genomes, has been updated to reflect recent advances in understanding signal transduction events on a whole-genome scale. Sentra consists of two principal components, a manually curated list of signal transduction proteins in 202 completely sequenced prokaryotic genomes and an automatically generated listing of predicted signaling proteins in 235 sequenced genomes that are awaiting manual curation. In addition to two-component histidine kinases and response regulators, the database now lists manually curated Ser/Thr/Tyr protein kinases and protein phosphatases, as well as adenylate and diguanylate cyclases and c-di-GMP phosphodiesterases, as defined in several recent reviews. All entries in Sentra are extensively annotated with relevant information from public databases (e.g. UniProt, KEGG, PDB and NCBI). Sentra's infrastructure was redesigned to support interactive cross-genome comparisons of signal transduction capabilities of prokaryotic organisms from a taxonomic and phenotypic perspective and in the framework of signal transduction pathways from KEGG. Sentra leverages the PUMA2 system to support interactive analysis and annotation of signal transduction proteins by the users.
Nucleic Acids Research 02/2007; 35(Database issue):D271-3. · 8.28 Impact Factor
[show abstract][hide abstract] ABSTRACT: GeNome Analysis Research Environment (GNARE) is a bioinformatics server that supports both auto-mated and interactive expert-driven analysis of user-submitted genomes and metagenomes. These analyses include gene function prediction and development of organism-specific metabolic reconstructions from sequence data. GNARE provides a framework for comparative and evolu-tionary analysis as well as annotation of genomes and metabolic networks in the context of phenoty-pic and taxonomic information. Results of analyses and metabolic models are visualized and extensively annotated with information from public databases. GNARE uses automated workflows and a Grid-based computational backend to perform high-throughput analysis of genomes. This use of distributed computing allows the analysis of an average-sized prokaryotic genome in less than 5 h.
Nucleic Acids Research 01/2007; · 8.28 Impact Factor
[show abstract][hide abstract] ABSTRACT: The PUMA2 system (available at http://compbio.mcs.anl.gov/puma2) is an interactive, integrated bioinformatics environment for high-throughput genetic sequence analysis and metabolic reconstructions from sequence data. PUMA2 provides a framework for comparative and evolutionary analysis of genomic data and metabolic networks in the context of taxonomic and phenotypic information. Grid infrastructure is used to perform computationally intensive tasks. PUMA2 currently contains precomputed analysis of 213 prokaryotic, 22 eukaryotic, 650 mitochondrial and 1493 viral genomes and automated metabolic reconstructions for >200 organisms. Genomic data is annotated with information integrated from >20 sequence, structural and metabolic databases and ontologies. PUMA2 supports both automated and interactive expert-driven annotation of genomes, using a variety of publicly available bioinformatics tools. It also contains a suite of unique PUMA2 tools for automated assignment of gene function, evolutionary analysis of protein families and comparative analysis of metabolic pathways. PUMA2 allows users to submit batch sequence data for automated functional analysis and construction of metabolic models. The results of these analyses are made available to the users in the PUMA2 environment for further interactive sequence analysis and annotation.
Nucleic Acids Research 01/2006; 34(Database issue):D369-72. · 8.28 Impact Factor
[show abstract][hide abstract] ABSTRACT: We have developed an interactive, integrated, bioinformat- ics environment to support biodefense and emerging in- fectious disease research. This environment has two components, PathoGene and Pathos. The PathoGene database is a comprehensive database of pathogenic pathways and related components containing information extracted from the literature. This resource contains graphical representation of the pathways of pathogenesis derived from the literature. PathoGene provides a knowl- edge base for the Pathos database. Pathos database is an integrated computational environment for genetic se- quence analysis and metabolic reconstructions from se- quence data. Pathos currently contains pre-computed analysis of over 170 complete genomes and over 135 automated metabolic reconstructions for completely se- quence pathogenic organisms. It also allows interactive comparative analysis of genomes and metabolic networks in the framework of taxonomic and phenotypic information. Pathos and PathoGene databases are freely available at http://compbio.mcs.anl.gov/pathos.