iCAVE: an open source tool for visualizing biomolecular networks in 3D, stereoscopic 3D and immersive 3D
Abstract Visualizations of biomolecular networks assist in systems-level data exploration in many cellular processes. Data generated from high-throughput experiments increasingly inform these networks, yet current tools do not adequately scale with concomitant increase in their size and complexity....
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Veröffentlicht in: | Gigascience 2017-08, Vol.6 (8), p.1-13 |
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creator | Liluashvili, Vaja Kalayci, Selim Fluder, Eugene Wilson, Manda Gabow, Aaron Gümüş, Zeynep H. |
description | Abstract
Visualizations of biomolecular networks assist in systems-level data exploration in many cellular processes. Data generated from high-throughput experiments increasingly inform these networks, yet current tools do not adequately scale with concomitant increase in their size and complexity. We present an open source software platform, interactome-CAVE (iCAVE), for visualizing large and complex biomolecular interaction networks in 3D. Users can explore networks (i) in 3D using a desktop, (ii) in stereoscopic 3D using 3D-vision glasses and a desktop, or (iii) in immersive 3D within a CAVE environment. iCAVE introduces 3D extensions of known 2D network layout, clustering, and edge-bundling algorithms, as well as new 3D network layout algorithms. Furthermore, users can simultaneously query several built-in databases within iCAVE for network generation or visualize their own networks (e.g., disease, drug, protein, metabolite). iCAVE has modular structure that allows rapid development by addition of algorithms, datasets, or features without affecting other parts of the code. Overall, iCAVE is the first freely available open source tool that enables 3D (optionally stereoscopic or immersive) visualizations of complex, dense, or multi-layered biomolecular networks. While primarily designed for researchers utilizing biomolecular networks, iCAVE can assist researchers in any field. |
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Visualizations of biomolecular networks assist in systems-level data exploration in many cellular processes. Data generated from high-throughput experiments increasingly inform these networks, yet current tools do not adequately scale with concomitant increase in their size and complexity. We present an open source software platform, interactome-CAVE (iCAVE), for visualizing large and complex biomolecular interaction networks in 3D. Users can explore networks (i) in 3D using a desktop, (ii) in stereoscopic 3D using 3D-vision glasses and a desktop, or (iii) in immersive 3D within a CAVE environment. iCAVE introduces 3D extensions of known 2D network layout, clustering, and edge-bundling algorithms, as well as new 3D network layout algorithms. Furthermore, users can simultaneously query several built-in databases within iCAVE for network generation or visualize their own networks (e.g., disease, drug, protein, metabolite). iCAVE has modular structure that allows rapid development by addition of algorithms, datasets, or features without affecting other parts of the code. Overall, iCAVE is the first freely available open source tool that enables 3D (optionally stereoscopic or immersive) visualizations of complex, dense, or multi-layered biomolecular networks. While primarily designed for researchers utilizing biomolecular networks, iCAVE can assist researchers in any field.</description><identifier>ISSN: 2047-217X</identifier><identifier>EISSN: 2047-217X</identifier><identifier>DOI: 10.1093/gigascience/gix054</identifier><identifier>PMID: 28814063</identifier><language>eng</language><publisher>United States: Oxford University Press</publisher><subject>Algorithms ; Animals ; Cellular communication ; Clustering ; Complexity ; Computational Biology - methods ; Databases, Factual ; Gene Regulatory Networks ; Humans ; Layouts ; Metabolic Networks and Pathways ; Metabolites ; Modular structures ; Multilayers ; Networks ; Open source software ; Protein Interaction Maps ; Signal Transduction ; Software ; Stereoscopy ; Technical Note ; User-Computer Interface</subject><ispartof>Gigascience, 2017-08, Vol.6 (8), p.1-13</ispartof><rights>The Authors 2017. Published by Oxford University Press. 2017</rights><rights>The Authors 2017. Published by Oxford University Press.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c468t-300163b894a145f930dd5c2ea4627e782f052a7bc59d1380186a1d33969dc57c3</citedby><cites>FETCH-LOGICAL-c468t-300163b894a145f930dd5c2ea4627e782f052a7bc59d1380186a1d33969dc57c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5554349/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5554349/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,1604,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28814063$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Liluashvili, Vaja</creatorcontrib><creatorcontrib>Kalayci, Selim</creatorcontrib><creatorcontrib>Fluder, Eugene</creatorcontrib><creatorcontrib>Wilson, Manda</creatorcontrib><creatorcontrib>Gabow, Aaron</creatorcontrib><creatorcontrib>Gümüş, Zeynep H.</creatorcontrib><title>iCAVE: an open source tool for visualizing biomolecular networks in 3D, stereoscopic 3D and immersive 3D</title><title>Gigascience</title><addtitle>Gigascience</addtitle><description>Abstract
Visualizations of biomolecular networks assist in systems-level data exploration in many cellular processes. Data generated from high-throughput experiments increasingly inform these networks, yet current tools do not adequately scale with concomitant increase in their size and complexity. We present an open source software platform, interactome-CAVE (iCAVE), for visualizing large and complex biomolecular interaction networks in 3D. Users can explore networks (i) in 3D using a desktop, (ii) in stereoscopic 3D using 3D-vision glasses and a desktop, or (iii) in immersive 3D within a CAVE environment. iCAVE introduces 3D extensions of known 2D network layout, clustering, and edge-bundling algorithms, as well as new 3D network layout algorithms. Furthermore, users can simultaneously query several built-in databases within iCAVE for network generation or visualize their own networks (e.g., disease, drug, protein, metabolite). iCAVE has modular structure that allows rapid development by addition of algorithms, datasets, or features without affecting other parts of the code. Overall, iCAVE is the first freely available open source tool that enables 3D (optionally stereoscopic or immersive) visualizations of complex, dense, or multi-layered biomolecular networks. While primarily designed for researchers utilizing biomolecular networks, iCAVE can assist researchers in any field.</description><subject>Algorithms</subject><subject>Animals</subject><subject>Cellular communication</subject><subject>Clustering</subject><subject>Complexity</subject><subject>Computational Biology - methods</subject><subject>Databases, Factual</subject><subject>Gene Regulatory Networks</subject><subject>Humans</subject><subject>Layouts</subject><subject>Metabolic Networks and Pathways</subject><subject>Metabolites</subject><subject>Modular structures</subject><subject>Multilayers</subject><subject>Networks</subject><subject>Open source software</subject><subject>Protein Interaction Maps</subject><subject>Signal Transduction</subject><subject>Software</subject><subject>Stereoscopy</subject><subject>Technical Note</subject><subject>User-Computer Interface</subject><issn>2047-217X</issn><issn>2047-217X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>TOX</sourceid><sourceid>EIF</sourceid><recordid>eNqNkU1PFTEUhhujEQL8ARemiRsXjPRz2nFhQi6oJCRuhLhrejtnLsWZdmxnLh-_3pKL5OKKbnpy-pw35-2L0DtKPlHS8KOVX9nsPAQHpb4lUrxCu4wIVTGqfr3eqnfQQc7XpByltFb8LdphWlNBar6Lrvzi-PL0M7YBxxECznFODvAUY4-7mPDa59n2_t6HFV76OMQe3NzbhANMNzH9ztgHzE8OcZ4gQcwujt6VRhFssR8GSNmvoTT20ZvO9hkOHu89dPH19Ofie3X-49vZ4vi8cqLWU8UJoTVf6kZYKmTXcNK20jGwomYKlGYdkcyqpZNNS7kmVNeWtpw3ddM6qRzfQ182uuO8HKB1EKZkezMmP9h0Z6L15vlL8FdmFddGSim4aIrAx0eBFP_MkCcz-Oyg722AOGdDy05CM6Uf0A__odfl-0KxZ5iiDamLFV0otqFcijkn6J6WocQ8ZGm2sjSbLMvQ-20bTyP_kitAtQHiPL5E8C-2Xq3y</recordid><startdate>20170801</startdate><enddate>20170801</enddate><creator>Liluashvili, Vaja</creator><creator>Kalayci, Selim</creator><creator>Fluder, Eugene</creator><creator>Wilson, Manda</creator><creator>Gabow, Aaron</creator><creator>Gümüş, Zeynep H.</creator><general>Oxford University Press</general><scope>TOX</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>JQ2</scope><scope>K9.</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20170801</creationdate><title>iCAVE: an open source tool for visualizing biomolecular networks in 3D, stereoscopic 3D and immersive 3D</title><author>Liluashvili, Vaja ; Kalayci, Selim ; Fluder, Eugene ; Wilson, Manda ; Gabow, Aaron ; Gümüş, Zeynep H.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c468t-300163b894a145f930dd5c2ea4627e782f052a7bc59d1380186a1d33969dc57c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Algorithms</topic><topic>Animals</topic><topic>Cellular communication</topic><topic>Clustering</topic><topic>Complexity</topic><topic>Computational Biology - methods</topic><topic>Databases, Factual</topic><topic>Gene Regulatory Networks</topic><topic>Humans</topic><topic>Layouts</topic><topic>Metabolic Networks and Pathways</topic><topic>Metabolites</topic><topic>Modular structures</topic><topic>Multilayers</topic><topic>Networks</topic><topic>Open source software</topic><topic>Protein Interaction Maps</topic><topic>Signal Transduction</topic><topic>Software</topic><topic>Stereoscopy</topic><topic>Technical Note</topic><topic>User-Computer Interface</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liluashvili, Vaja</creatorcontrib><creatorcontrib>Kalayci, Selim</creatorcontrib><creatorcontrib>Fluder, Eugene</creatorcontrib><creatorcontrib>Wilson, Manda</creatorcontrib><creatorcontrib>Gabow, Aaron</creatorcontrib><creatorcontrib>Gümüş, Zeynep H.</creatorcontrib><collection>Oxford Journals Open Access Collection</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Gigascience</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liluashvili, Vaja</au><au>Kalayci, Selim</au><au>Fluder, Eugene</au><au>Wilson, Manda</au><au>Gabow, Aaron</au><au>Gümüş, Zeynep H.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>iCAVE: an open source tool for visualizing biomolecular networks in 3D, stereoscopic 3D and immersive 3D</atitle><jtitle>Gigascience</jtitle><addtitle>Gigascience</addtitle><date>2017-08-01</date><risdate>2017</risdate><volume>6</volume><issue>8</issue><spage>1</spage><epage>13</epage><pages>1-13</pages><issn>2047-217X</issn><eissn>2047-217X</eissn><abstract>Abstract
Visualizations of biomolecular networks assist in systems-level data exploration in many cellular processes. Data generated from high-throughput experiments increasingly inform these networks, yet current tools do not adequately scale with concomitant increase in their size and complexity. We present an open source software platform, interactome-CAVE (iCAVE), for visualizing large and complex biomolecular interaction networks in 3D. Users can explore networks (i) in 3D using a desktop, (ii) in stereoscopic 3D using 3D-vision glasses and a desktop, or (iii) in immersive 3D within a CAVE environment. iCAVE introduces 3D extensions of known 2D network layout, clustering, and edge-bundling algorithms, as well as new 3D network layout algorithms. Furthermore, users can simultaneously query several built-in databases within iCAVE for network generation or visualize their own networks (e.g., disease, drug, protein, metabolite). iCAVE has modular structure that allows rapid development by addition of algorithms, datasets, or features without affecting other parts of the code. Overall, iCAVE is the first freely available open source tool that enables 3D (optionally stereoscopic or immersive) visualizations of complex, dense, or multi-layered biomolecular networks. While primarily designed for researchers utilizing biomolecular networks, iCAVE can assist researchers in any field.</abstract><cop>United States</cop><pub>Oxford University Press</pub><pmid>28814063</pmid><doi>10.1093/gigascience/gix054</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Animals Cellular communication Clustering Complexity Computational Biology - methods Databases, Factual Gene Regulatory Networks Humans Layouts Metabolic Networks and Pathways Metabolites Modular structures Multilayers Networks Open source software Protein Interaction Maps Signal Transduction Software Stereoscopy Technical Note User-Computer Interface |
title | iCAVE: an open source tool for visualizing biomolecular networks in 3D, stereoscopic 3D and immersive 3D |
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