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      iPath2.0: interactive pathway explorer

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          Abstract

          iPath2.0 is a web-based tool ( http://pathways.embl.de) for the visualization and analysis of cellular pathways. Its primary map summarizes the metabolism in biological systems as annotated to date. Nodes in the map correspond to various chemical compounds and edges represent series of enzymatic reactions. In two other maps, iPath2.0 provides an overview of secondary metabolite biosynthesis and a hand-picked selection of important regulatory pathways and other functional modules, allowing a more general overview of protein functions in a genome or metagenome. iPath2.0′s main interface is an interactive Flash-based viewer, which allows users to easily navigate and explore the complex pathway maps. In addition to the default pre-computed overview maps, iPath offers several data mapping tools. Users can upload various types of data and completely customize all nodes and edges of iPath2.0′s maps. These customized maps give users an intuitive overview of their own data, guiding the analysis of various genomics and metagenomics projects.

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          Integration of biological networks and gene expression data using Cytoscape.

          Melissa Cline, Michael Smoot, Ethan Cerami … (2007)
          Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape.
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            KEGG Atlas mapping for global analysis of metabolic pathways

            Shujiro Okuda, Takuji Yamada, Masami Hamajima … (2008)
            KEGG Atlas is a new graphical interface to the KEGG suite of databases, especially to the systems information in the PATHWAY and BRITE databases. It currently consists of a single global map and an associated viewer for metabolism, covering about 120 KEGG metabolic pathway maps and about 10 BRITE hierarchies. The viewer allows the user to navigate and zoom the global map under the Ajax technology. The mapping of high-throughput experimental data onto the global map is the main use of KEGG Atlas. In the global metabolism map, the node (circle) is a chemical compound and the edge (line) is a set of reactions linked to a set of KEGG Orthology (KO) entries for enzyme genes. Once gene identifiers in different organisms are converted to the K number identifiers in the KO system, corresponding line segments can be highlighted in the global map, allowing the user to view genome sequence data as organism-specific pathways, gene expression data as up- or down-regulated pathways, etc. Once chemical compounds are converted to the C number identifiers in KEGG, metabolomics data can also be displayed in the global map. KEGG Atlas is available at http://www.genome.jp/kegg/atlas/.
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              eggNOG v2.0: extending the evolutionary genealogy of genes with enhanced non-supervised orthologous groups, species and functional annotations

              J. Müller, D. Szklarczyk, J Julien … (2010)
              The identification of orthologous relationships forms the basis for most comparative genomics studies. Here, we present the second version of the eggNOG database, which contains orthologous groups (OGs) constructed through identification of reciprocal best BLAST matches and triangular linkage clustering. We applied this procedure to 630 complete genomes (529 bacteria, 46 archaea and 55 eukaryotes), which is a 2-fold increase relative to the previous version. The pipeline yielded 224 847 OGs, including 9724 extended versions of the original COG and KOG. We computed OGs for different levels of the tree of life; in addition to the species groups included in our first release (i.e. fungi, metazoa, insects, vertebrates and mammals), we have now constructed OGs for archaea, fishes, rodents and primates. We automatically annotate the non-supervised orthologous groups (NOGs) with functional descriptions, protein domains, and functional categories as defined initially for the COG/KOG database. In-depth analysis is facilitated by precomputed high-quality multiple sequence alignments and maximum-likelihood trees for each of the available OGs. Altogether, eggNOG covers 2 242 035 proteins (built from 2 590 259 proteins) and provides a broad functional description for at least 1 966 709 (88%) of them. Users can access the complete set of orthologous groups via a web interface at: http://eggnog.embl.de.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Nucleic Acids Res
                Journal ID (publisher-id): nar
                Journal ID (hwp): nar
                Title: Nucleic Acids Research
                Publisher: Oxford University Press
                ISSN (Print): 0305-1048
                ISSN (Electronic): 1362-4962
                Publication date Collection: 1 July 2011
                Publication date (Print): 1 July 2011
                Publication date (Electronic): 5 May 2011
                Publication date PMC-release: 5 May 2011
                Volume: 39
                Issue: Web Server issue , Web Server issue
                Pages: W412-W415
                Affiliations
                1EMBL, Meyerhofstrasse 1, 69117 Heidelberg, Germany, 2Department of Bioinformatics, College of Life Sciences, Ritsumeikan University, 1-1-1 Nojihigashi, Kusatsu, Shiga 525-8577 and 3Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan
                Author notes
                *To whom correspondence should be addressed. Tel: +49 6221 387 8526; Fax: +49 6221 387 517; Email: bork@ 123456embl.de

                The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.

                Article
                Publisher ID: gkr313
                DOI: 10.1093/nar/gkr313
                PMC ID: 3125749
                PubMed ID: 21546551
                SO-VID: 19495991-a2ad-47ee-bab6-56076484033f
                Copyright © © The Author(s) 2011. Published by Oxford University Press.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 20 February 2011
                Date revision received : 31 March 2011
                Date accepted : 18 April 2011
                Page count
                Pages: 4
                Categories
                Subject: Articles

                ScienceOpen disciplines: Genetics
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                ScienceOpen disciplines: Genetics

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