9 research outputs found
BioIMAX : a Web2.0 approach to visual data mining in bioimage data
Loyek C. BioIMAX : a Web2.0 approach to visual data mining in bioimage data. Bielefeld: Universität Bielefeld; 2012
A Web2.0 Strategy for the Collaborative Analysis of Complex Bioimages
Loyek C, Kölling J, Langenkämper D, Niehaus K, Nattkemper TW. A Web2.0 Strategy for the Collaborative Analysis of Complex Bioimages. In: Gama J, Bradley E, Hollmén J, eds. Advances in Intelligent Data Analysis X: 10th International Symposium, IDA 2011, Porto, Portugal, October 29-31, 2011. Proceedings. Lecture Notes in Computer Science. Vol 7014. Berlin, Heidelberg: Springer; 2011: 258-269
Multivariate Image Mining
Herold J, Loyek C, Nattkemper TW. Multivariate Image Mining. Wiley Interdisciplinary Reviews: DATA MINING AND KNOWLEDGE DISCOVERY. 2011;1(1):2-13
Web2.0 paves new ways for collaborative and exploratory analysis of Chemical Compounds in Spectrometry Data
Loyek C, Bunkowski A, Vautz W, Nattkemper TW. Web2.0 paves new ways for collaborative and exploratory analysis of Chemical Compounds in Spectrometry Data. Journal of Integrative Bioinformatics. 2011;8(2):158.In nowadays life science projects, sharing data and data interpretation is becoming increasingly important. This considerably calls for novel information technology approaches, which enable the integration of expert knowledge from different disciplines in combination with advanced data analysis facilities in a collaborative manner. Since the recent development of web technologies offers scientific communities new ways for cooperation and communication, we propose a fully web-based software approach for the collaborative analysis of bioimage data and demonstrate the applicability of Web2.0 techniques to ion mobility spectrometry image data. Our approach allows collaborating experts to easily share, explore and discuss complex image data without any installation of software packages. Scientists only need a username and a password to get access to our system and can directly start exploring and analyzing their data
Web2.0 paves new ways for collaborative and exploratory analysis of Chemical Compounds in Spectrometry Data
In nowadays life science projects, sharing data and data interpretation is becoming increasingly important. This considerably calls for novel information technology approaches, which enable the integration of expert knowledge from different disciplines in combination with advanced data analysis facilities in a collaborative manner. Since the recent development of web technologies offers scientific communities new ways for cooperation and communication, we propose a fully web-based software approach for the collaborative analysis of bioimage data and demonstrate the applicability of Web2.0 techniques to ion mobility spectrometry image data. Our approach allows collaborating experts to easily share, explore and discuss complex image data without any installation of software packages. Scientists only need a username and a password to get access to our system and can directly start exploring and analyzing their data
BioIMAX : a web 2.0 approach for easy exploratory and collaborative access to multivariate bioimage data
Background: Innovations in biological and biomedical imaging produce complex high-content and multivariate
image data. For decision-making and generation of hypotheses, scientists need novel information technology tools
that enable them to visually explore and analyze the data and to discuss and communicate results or findings with
collaborating experts from various places.
Results: In this paper, we present a novel Web2.0 approach, BioIMAX, for the collaborative exploration and analysis
of multivariate image data by combining the webs collaboration and distribution architecture with the interface
interactivity and computation power of desktop applications, recently called rich internet application.
Conclusions: BioIMAX allows scientists to discuss and share data or results with collaborating experts and to
visualize, annotate, and explore multivariate image data within one web-based platform from any location via a
standard web browser requiring only a username and a password. BioIMAX can be accessed at http://ani.cebitec.
uni-bielefeld.de/BioIMAX with the username “test” and the password “test1” for testing purposes
Content Based Image Retrieval for Dynamic Time Series Data
Lessmann B, Nattkemper TW, Huth J, et al. Content Based Image Retrieval for Dynamic Time Series Data. In: Proceedings of BVM. 2006: 61-65