Visualization methods of hierarchical biological data

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Kuznetsova, Irina
dc.contributor.author Lugmayr, Artur
dc.contributor.author Holzinger, Andreas
dc.date.accessioned 2018-12-10T10:35:01Z
dc.date.available 2018-12-10T10:35:01Z
dc.date.issued 2017-01-01
dc.identifier.citation Kuznetsova , I , Lugmayr , A & Holzinger , A 2017 , Visualization methods of hierarchical biological data : A survey and review . in 7th International Workshop on Semantic Ambient Media Experiences, SAME 2014 : Ambient Media Usability, Interaction and Smart Media Technologies . 2 edn , vol. 2017 , International series on information systems and management in creative eMedia , no. 2 , vol. 2017 , International Ambient Media Association (iAMEA) , pp. 32-39 , International Workshop on Semantic Ambient Media Experiences , Bangkok , Thailand , 27/11/2017 . en
dc.identifier.isbn 9781510800168
dc.identifier.issn 2341-5584
dc.identifier.issn 2341-5576
dc.identifier.other PURE UUID: f0990a17-b1de-4869-8fac-b3492b70bce4
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/visualization-methods-of-hierarchical-biological-data(f0990a17-b1de-4869-8fac-b3492b70bce4).html
dc.identifier.other PURE LINK: http://www.scopus.com/inward/record.url?scp=85045210728&partnerID=8YFLogxK
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/28853528/283_1_717_2_10_20180201.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/35348
dc.description.abstract The sheer amount of high dimensional biomedical data requires machine learning, and advanced data visualization techniques to make the data understandable for human experts. Most biomedical data today is in arbitrary high dimensional spaces, and is not directly accessible to the human expert for a visual and interactive analysis process. To cope with this challenge, the application of machine learning and knowledge extraction methods is indispensable throughout the entire data analysis workflow. Nevertheless, human experts need to understand and interpret the data and experimental results. Appropriate understanding is typically supported by visualizing the results adequately, which is not a simple task. Consequently, data visualization is one of the most crucial steps in conveying biomedical results. It can and should be considered as a critical part of the analysis pipeline. Still as of today, 2D representations dominate, and human perception is limited to this lower dimension to understand the data. This makes the visualization of the results in an understandable and comprehensive manner a grand challenge. This paper reviews the current state of visualization methods in a biomedical context. It focuses on hierarchical biological data as a source for visualization, and gives a comprehensive survey of visualization techniques for this particular type of data. en
dc.format.extent 8
dc.format.extent 32-39
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Ambient Media Association
dc.relation.ispartof International Workshop on Semantic Ambient Media Experiences en
dc.relation.ispartofseries 7th International Workshop on Semantic Ambient Media Experiences, SAME 2014 en
dc.relation.ispartofseries Volume 2017, issue 2 en
dc.relation.ispartofseries International series on information systems and management in creative eMedia en
dc.rights openAccess en
dc.subject.other Computer Networks and Communications en
dc.subject.other Media Technology en
dc.subject.other 6132 Visual arts and design en
dc.title Visualization methods of hierarchical biological data en
dc.type A4 Artikkeli konferenssijulkaisussa fi
dc.description.version Peer reviewed en
dc.contributor.department Medical University of Graz
dc.contributor.department Department of Film, Television and Scenography
dc.subject.keyword Big data
dc.subject.keyword Bioinformatics
dc.subject.keyword Computer graphics
dc.subject.keyword Hierarchical data
dc.subject.keyword Information visualization
dc.subject.keyword Visualization
dc.subject.keyword Computer Networks and Communications
dc.subject.keyword Media Technology
dc.subject.keyword 6132 Visual arts and design
dc.identifier.urn URN:NBN:fi:aalto-201812106363
dc.type.version publishedVersion


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