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Visualization of Biological Data - Crossroads (Dagstuhl Seminar 18161)

Authors: Jan Aerts, Nils Gehlenborg, Georgeta Elisabeta Marai, and Kay Katja Nieselt

Published in: Dagstuhl Reports, Volume 8, Issue 4 (2018)


Abstract
Our ability to generate and collect biological data has accelerated significantly in the past two decades. In response, many novel computational and statistical analysis techniques have been developed to process and integrate biological data sets. However, in addition to computational and statistical approaches, visualization techniques are needed to enable the interpretation of data as well as the communication of results. The design and implementation of such techniques lies at the intersection of the biology, bioinformatics, and data visualization fields. The purpose of Dagstuhl Seminar 18161 "Visualization of Biological Data - Crossroads" was to bring together researchers from all three fields, to identify opportunities and challenges, and to develop a path forward for biological data visualization research.

Cite as

Jan Aerts, Nils Gehlenborg, Georgeta Elisabeta Marai, and Kay Katja Nieselt. Visualization of Biological Data - Crossroads (Dagstuhl Seminar 18161). In Dagstuhl Reports, Volume 8, Issue 4, pp. 32-71, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)


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@Article{aerts_et_al:DagRep.8.4.32,
  author =	{Aerts, Jan and Gehlenborg, Nils and Marai, Georgeta Elisabeta and Nieselt, Kay Katja},
  title =	{{Visualization of Biological Data - Crossroads (Dagstuhl Seminar 18161)}},
  pages =	{32--71},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2018},
  volume =	{8},
  number =	{4},
  editor =	{Aerts, Jan and Gehlenborg, Nils and Marai, Georgeta Elisabeta and Nieselt, Kay Katja},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.8.4.32},
  URN =		{urn:nbn:de:0030-drops-97600},
  doi =		{10.4230/DagRep.8.4.32},
  annote =	{Keywords: imaging, omics, sequence analysis, visual analytics, visualisation}
}
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