WHIDE - A web tool for visual data mining colocation patterns in multivariate bioimages

Kölling J, Langenkämper D, Sylvie A, Michale K, Nattkemper TW (2012)
Bioinformatics 28(8): 1143-1150.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
Download
OA
Autor/in
Abstract / Bemerkung
Motivation: Bioimaging techniques rapidly develop towards higher resolution and dimension. The increase in dimension is achieved by different techniques such as multi-tag fluorescence imaging, MALDI imaging or Raman imaging, which record for each pixel a N dimensional intensity array, representing local abundances of molecules, residues or interaction patterns. The analysis of such multivariate bioimages (MBI) calls for new approaches to support users in the analysis of both feature domains: space (i.e. sample morphology) and molecular colocation or interaction. In this paper we present our approach WHIDE (Web-based Hyperbolic Image Data Explorer) that combines principles from computational learning, dimension reduction and visualization in a free web application. Results: We applied WHIDE to a set of MBI recorded using the multi-tag fluorescence imaging TIS (Toponome Imaging System). The MBI show FOV in tissue sections from a colon cancer study and we compare tissue from normal / healthy colon with tissue classified as tumor. Our results show, that WHIDE efficiently reduces the complexity of the data by mapping each of the pixels to a cluster, referred to as MCEP (Molecular Co-Expression Phenotypes) and provides a structural basis for a sophisticated multi-modal visualization, which combines topology preserving pseudocoloring with information visualization. The wide range of WHIDE’s applicability is demonstrated with examples from toponome imaging, high content screens and MALDI imaging (shown in the Supplementary).
Stichworte
medical imaging; web technology; MALDI imaging; rich internet application; Bioimage Informatics; proteomics; multi-tag fluorescence microscopy; metabolomics; imaging; visualization; information visualization; image analysis; biodata mining; dimension reduction; bioimax; neural networks
Erscheinungsjahr
2012
Zeitschriftentitel
Bioinformatics
Band
28
Ausgabe
8
Seite(n)
1143-1150
ISSN
1367-4803
eISSN
1460-2059
Page URI
https://pub.uni-bielefeld.de/record/2481783

Zitieren

Kölling J, Langenkämper D, Sylvie A, Michale K, Nattkemper TW. WHIDE - A web tool for visual data mining colocation patterns in multivariate bioimages. Bioinformatics. 2012;28(8):1143-1150.
Kölling, J., Langenkämper, D., Sylvie, A., Michale, K., & Nattkemper, T. W. (2012). WHIDE - A web tool for visual data mining colocation patterns in multivariate bioimages. Bioinformatics, 28(8), 1143-1150. doi:10.1093/bioinformatics/bts104
Kölling, J., Langenkämper, D., Sylvie, A., Michale, K., and Nattkemper, T. W. (2012). WHIDE - A web tool for visual data mining colocation patterns in multivariate bioimages. Bioinformatics 28, 1143-1150.
Kölling, J., et al., 2012. WHIDE - A web tool for visual data mining colocation patterns in multivariate bioimages. Bioinformatics, 28(8), p 1143-1150.
J. Kölling, et al., “WHIDE - A web tool for visual data mining colocation patterns in multivariate bioimages”, Bioinformatics, vol. 28, 2012, pp. 1143-1150.
Kölling, J., Langenkämper, D., Sylvie, A., Michale, K., Nattkemper, T.W.: WHIDE - A web tool for visual data mining colocation patterns in multivariate bioimages. Bioinformatics. 28, 1143-1150 (2012).
Kölling, Jan, Langenkämper, Daniel, Sylvie, Abouna, Michale, Khan, and Nattkemper, Tim Wilhelm. “WHIDE - A web tool for visual data mining colocation patterns in multivariate bioimages”. Bioinformatics 28.8 (2012): 1143-1150.
Alle Dateien verfügbar unter der/den folgenden Lizenz(en):
Copyright Statement:
This Item is protected by copyright and/or related rights. [...]
Volltext(e)
Access Level
OA Open Access
Zuletzt Hochgeladen
2019-09-06T09:18:00Z
MD5 Prüfsumme
49d977a2f5f42ad2d49320199e6ccc5c

Link(s) zu Volltext(en)
Access Level
Restricted Closed Access

Export

Markieren/ Markierung löschen
Markierte Publikationen

Open Data PUB

Web of Science

Dieser Datensatz im Web of Science®

Quellen

PMID: 22390938
PubMed | Europe PMC

Suchen in

Google Scholar