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  1. Article ; Online: Analysis and Visualization of Dynamic Networks Using the DyNet App for Cytoscape.

    Salamon, John / Goenawan, Ivan H / Lynn, David J

    Current protocols in bioinformatics

    2018  Volume 63, Issue 1, Page(s) e55

    Abstract: Biological processes are regulated at a cellular level by tightly controlled molecular interaction networks, which are collectively known as the interactome. The interactome is not a static entity, but instead is dynamically reorganized or "rewired" ... ...

    Abstract Biological processes are regulated at a cellular level by tightly controlled molecular interaction networks, which are collectively known as the interactome. The interactome is not a static entity, but instead is dynamically reorganized or "rewired" under varying temporal, spatial, and environmental conditions. Most network analysis and visualization tools have, to date, been developed for static representations of molecular interaction data. Here, we describe a protocol that provides a step-by-step guide to DyNet, a Cytoscape 3 application that facilitates the visualization and analysis of dynamic molecular interaction networks. DyNet represents a dynamic network as a set of state graphs that are synchronized in their layout. This synchronization is managed in real time and is automatically updated when a graph is manipulated by a user (e.g., dragging, zooming, moving a node). DyNet also provides several statistical tools enabling users to quickly identify and analyze the most 'rewired' nodes across many network states. © 2018 by John Wiley & Sons, Inc.
    MeSH term(s) Computational Biology/methods ; Gene Regulatory Networks ; Software
    Language English
    Publishing date 2018-08-31
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 1934-340X
    ISSN (online) 1934-340X
    DOI 10.1002/cpbi.55
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: DyNet: visualization and analysis of dynamic molecular interaction networks.

    Goenawan, Ivan H / Bryan, Kenneth / Lynn, David J

    Bioinformatics (Oxford, England)

    2016  Volume 32, Issue 17, Page(s) 2713–2715

    Abstract: Unlabelled: : The ability to experimentally determine molecular interactions on an almost proteome-wide scale under different conditions is enabling researchers to move from static to dynamic network analysis, uncovering new insights into how ... ...

    Abstract Unlabelled: : The ability to experimentally determine molecular interactions on an almost proteome-wide scale under different conditions is enabling researchers to move from static to dynamic network analysis, uncovering new insights into how interaction networks are physically rewired in response to different stimuli and in disease. Dynamic interaction data presents a special challenge in network biology. Here, we present DyNet, a Cytoscape application that provides a range of functionalities for the visualization, real-time synchronization and analysis of large multi-state dynamic molecular interaction networks enabling users to quickly identify and analyze the most 'rewired' nodes across many network states.
    Availability and implementation: DyNet is available at the Cytoscape (3.2+) App Store (http://apps.cytoscape.org/apps/dynet).
    Contact: david.lynn@sahmri.com
    Supplementary information: Supplementary data are available at Bioinformatics online.
    MeSH term(s) Computational Biology ; Gene Regulatory Networks ; Genomics ; Humans ; Metabolic Networks and Pathways ; Software
    Language English
    Publishing date 2016-09-01
    Publishing country England
    Document type Journal Article
    ZDB-ID 1422668-6
    ISSN 1367-4811 ; 1367-4803
    ISSN (online) 1367-4811
    ISSN 1367-4803
    DOI 10.1093/bioinformatics/btw187
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article: DyNet: visualization and analysis of dynamic molecular interaction networks

    Goenawan, Ivan H / Bryan, Kenneth / Lynn, David J

    Bioinformatics. 2016 Sept. 01, v. 32, no. 17

    2016  

    Abstract: Summary : The ability to experimentally determine molecular interactions on an almost proteome-wide scale under different conditions is enabling researchers to move from static to dynamic network analysis, uncovering new insights into how interaction ... ...

    Abstract Summary : The ability to experimentally determine molecular interactions on an almost proteome-wide scale under different conditions is enabling researchers to move from static to dynamic network analysis, uncovering new insights into how interaction networks are physically rewired in response to different stimuli and in disease. Dynamic interaction data presents a special challenge in network biology. Here, we present DyNet, a Cytoscape application that provides a range of functionalities for the visualization, real-time synchronization and analysis of large multi-state dynamic molecular interaction networks enabling users to quickly identify and analyze the most ‘rewired’ nodes across many network states. Availability and Implementation : DyNet is available at the Cytoscape (3.2+) App Store (http://apps.cytoscape.org/apps/dynet). Contact : david.lynn@sahmri.com . Supplementary Information : Supplementary data are available at Bioinformatics online.
    Keywords bioinformatics ; computer analysis ; computer software ; molecular biology
    Language English
    Dates of publication 2016-0901
    Size p. 2713-2715.
    Publishing place Oxford University Press
    Document type Article
    ZDB-ID 1468345-3
    ISSN 1460-2059 ; 1367-4811 ; 1367-4803
    ISSN (online) 1460-2059 ; 1367-4811
    ISSN 1367-4803
    DOI 10.1093/bioinformatics/btw187
    Database NAL-Catalogue (AGRICOLA)

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  4. Article: Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks.

    Muetze, Tanja / Goenawan, Ivan H / Wiencko, Heather L / Bernal-Llinares, Manuel / Bryan, Kenneth / Lynn, David J

    F1000Research

    2016  Volume 5, Page(s) 1745

    Abstract: Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, ... ...

    Abstract Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT), which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest, integrate contextual information, such as gene expression or mass spectrometry data, and identify hub nodes that are more highly connected to contextual nodes (e.g. genes or proteins that are differentially expressed) than expected by chance. In a case study, we use CHAT to construct a network of genes that are differentially expressed in Dengue fever, a viral infection. CHAT was used to identify and compare contextual and degree-based hubs in this network. The top 20 degree-based hubs were enriched in pathways related to the cell cycle and cancer, which is likely due to the fact that proteins involved in these processes tend to be highly connected in general. In comparison, the top 20 contextual hubs were enriched in pathways commonly observed in a viral infection including pathways related to the immune response to viral infection. This analysis shows that such
    Availability: CHAT is available for Cytoscape 3.0+ and can be installed via the Cytoscape App Store ( http://apps.cytoscape.org/apps/chat).
    Language English
    Publishing date 2016-07-19
    Publishing country England
    Document type Journal Article
    ZDB-ID 2699932-8
    ISSN 2046-1402
    ISSN 2046-1402
    DOI 10.12688/f1000research.9118.2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Contextual Hub Analysis Tool (CHAT)

    Tanja Muetze / Ivan H. Goenawan / Heather L. Wiencko / Manuel Bernal-Llinares / Kenneth Bryan / David J. Lynn

    F1000Research, Vol

    A Cytoscape app for identifying contextually relevant hubs in biological networks [version 2; referees: 2 approved]

    2016  Volume 5

    Abstract: Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, ... ...

    Abstract Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT), which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest, integrate contextual information, such as gene expression or mass spectrometry data, and identify hub nodes that are more highly connected to contextual nodes (e.g. genes or proteins that are differentially expressed) than expected by chance. In a case study, we use CHAT to construct a network of genes that are differentially expressed in Dengue fever, a viral infection. CHAT was used to identify and compare contextual and degree-based hubs in this network. The top 20 degree-based hubs were enriched in pathways related to the cell cycle and cancer, which is likely due to the fact that proteins involved in these processes tend to be highly connected in general. In comparison, the top 20 contextual hubs were enriched in pathways commonly observed in a viral infection including pathways related to the immune response to viral infection. This analysis shows that such contextual hubs are considerably more biologically relevant than degree-based hubs and that analyses which rely on the identification of hubs solely based on their connectivity may be biased towards nodes that are highly connected in general rather than in the specific context of interest. Availability: CHAT is available for Cytoscape 3.0+ and can be installed via the Cytoscape App Store (http://apps.cytoscape.org/apps/chat).
    Keywords Bioinformatics ; Tropical & Travel-Associated Diseases ; Medicine ; R ; Science ; Q
    Subject code 572
    Language English
    Publishing date 2016-08-01T00:00:00Z
    Publisher F1000 Research Ltd
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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