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MediVis 2017 - 13th International Conference BioMedical Visualization

Date2017-07-11 - 2017-07-14

Deadline2017-01-31

VenueLondon, England, UK - United Kingdom UK - United Kingdom

Keywords

Websitehttps://www.graphicslink.co.uk/IV2017

Topics/Call fo Papers

Organized as part of the 2017 International Information Visualisation Conference, the 21st International Symposium on Information Visualization in Biomedical Informatics (IVBI) is a forum for the presentation of original papers in information visualization theory and applications to biomedical and biomolecular data and processes. The symposium covers all aspects of visualization and issues affecting interaction with large and complex data sets. We encourage the submission of papers covering new techniques, old techniques applied in novel ways, new methods, interesting applications and in-depth surveys.
Peer-reviewed papers will be published in conference proceedings by The Conference Publishing Services (CPS) < http://www.computer.org/portal/web/cscps/>, with ISBN number, and will be indexed by major bibliographical search engines.
Examples of biomedical topics include, but are not limited to
High-performance computing and parallel rendering
Nucleotide and protein sequence alignment and search
Protein structure, function, sequence analysis
Signaling pathways, biochemical networks
Gene regulation, expression, identification and networks
DNA, RNA structure, function, sequence analysis
Biochemical and cellular simulations and models
Structural, functional and comparative genomics
Biomarkers
Drug design
Computer aided diagnosis
Examples of visualization topics include, but are not limited to:
Interaction with data sets, human factors
Data exploration using classical and novel approaches
Visualization and databases
Linking literature and semantics in pathway visualizations
Volume and flow visualization
Annotation and labelling
Overview and detail presentation of predictive or uncertain data
Comparative Methods / User studies / Surveys
Identification of correlated and anomalous relationships in disparate data sets

Last modified: 2016-12-21 14:48:47