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      BioPAXViz: a cytoscape application for the visual exploration of metabolic pathway evolution

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          Abstract

          BioPAXViz is a Cytoscape (version 3) application, providing a comprehensive framework for metabolic pathway visualization. Beyond the basic parsing, viewing and browsing roles, the main novel function that BioPAXViz provides is a visual comparative analysis of metabolic pathway topologies across pre-computed pathway phylogenomic profiles given a species phylogeny. Furthermore, BioPAXViz supports the display of hierarchical trees that allow efficient navigation through sets of variants of a single reference pathway. Thus, BioPAXViz can significantly facilitate, and contribute to, the study of metabolic pathway evolution and engineering.

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          Most cited references 11

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          BioPAX – A community standard for pathway data sharing

          BioPAX (Biological Pathway Exchange) is a standard language to represent biological pathways at the molecular and cellular level. Its major use is to facilitate the exchange of pathway data (http://www.biopax.org). Pathway data captures our understanding of biological processes, but its rapid growth necessitates development of databases and computational tools to aid interpretation. However, the current fragmentation of pathway information across many databases with incompatible formats presents barriers to its effective use. BioPAX solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. BioPAX was created through a community process. Through BioPAX, millions of interactions organized into thousands of pathways across many organisms, from a growing number of sources, are available. Thus, large amounts of pathway data are available in a computable form to support visualization, analysis and biological discovery.
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            Expansion of biological pathways based on evolutionary inference.

            The availability of diverse genomes makes it possible to predict gene function based on shared evolutionary history. This approach can be challenging, however, for pathways whose components do not exhibit a shared history but rather consist of distinct "evolutionary modules." We introduce a computational algorithm, clustering by inferred models of evolution (CLIME), which inputs a eukaryotic species tree, homology matrix, and pathway (gene set) of interest. CLIME partitions the gene set into disjoint evolutionary modules, simultaneously learning the number of modules and a tree-based evolutionary history that defines each module. CLIME then expands each module by scanning the genome for new components that likely arose under the inferred evolutionary model. Application of CLIME to ∼1,000 annotated human pathways and to the proteomes of yeast, red algae, and malaria reveals unanticipated evolutionary modularity and coevolving components. CLIME is freely available and should become increasingly powerful with the growing wealth of eukaryotic genomes.
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              Origin and evolution of metabolic pathways.

              The emergence and evolution of metabolic pathways represented a crucial step in molecular and cellular evolution. In fact, the exhaustion of the prebiotic supply of amino acids and other compounds that were likely present in the ancestral environment, imposed an important selective pressure, favoring those primordial heterotrophic cells which became capable of synthesizing those molecules. Thus, the emergence of metabolic pathways allowed primitive organisms to become increasingly less-dependent on exogenous sources of organic compounds. Comparative analyses of genes and genomes from organisms belonging to Archaea, Bacteria and Eukarya revealed that, during evolution, different forces and molecular mechanisms might have driven the shaping of genomes and the arisal of new metabolic abilities. Among these gene elongations, gene and operon duplications undoubtedly played a major role since they can lead to the (immediate) appearance of new genetic material that, in turn, might undergo evolutionary divergence giving rise to new genes coding for new metabolic abilities. Gene duplication has been invoked in the different schemes proposed to explain why and how the extant metabolic pathways have arisen and shaped. Both the analysis of completely sequenced genomes and directed evolution experiments strongly support one of them, i.e. the patchwork hypothesis, according to which metabolic pathways have been assembled through the recruitment of primitive enzymes that could react with a wide range of chemically related substrates. However, the analysis of the structure and organization of genes belonging to ancient metabolic pathways, such as histidine biosynthesis and nitrogen fixation, suggested that other different hypothesis, i.e. the retrograde hypothesis or the semi-enzymatic theory, may account for the arisal of some metabolic routes.
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                Author and article information

                Journal
                Bioinformatics
                Bioinformatics
                Oxford University Press (OUP)
                1367-4803
                1460-2059
                January 25 2017
                : btw813
                Article
                10.1093/bioinformatics/btw813
                28453679
                © 2017

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