Visual Analytics for Large and heterogeneous Life Science data with emphasis on expression data

Applicant:

Professor Dr. Gerik Scheuermann ¹⁾, Leipzig
Universität Leipzig
Institut für Informatik
Abteilung Bild- und Signalverarbeitung

Dr. Kay Nieselt, Tübingen
Eberhard-Karls-Universität Tübingen
Wilhelm-Schickard Institut für Informatik
Nachwuchsgruppe "Proteomics Algorithmen und Simulation"

Project:

Visual Analytics for Large and heterogeneous Life Science data with emphasis on expression data (Publications)

Summary:

The analysis of gene expression experiments on microarrays is challenging scientific endeavor, since it involves the scalable processing of very large, heterogeneous, incomplete, potentially conflicting, and potentially dynamic data. The relevant information (genes active in a biological process) is very difficult to extract and requires the support of automated extraction algorithms based on statistical computing. Unfortunately, the unsupervised application of these statistical measures does not guarantee the successful extraction of relevant information, but requires critical consideration itself. Hence, the use of powerful visualization methods is of central relevance. The scope of this project proposal is the application of the visual analytics paradigm for the analysis of complex microarray datasets. It combines novel visual exploration and interaction methods with advanced statistical computing to extract the relevant information from potentially huge datasets generated by high-throughput methods such as microarrays. Furthermore, methods from perception research will be applied to create a perception sensitive processing pipeline, including a psychophysical evaluation study on the created methodology. Preliminary results already indicate that this avenue will lead to an effective analysis and “enable profound insight” into the application domain. This visual analytics approach, combining visualization, interaction, data integration, and statistics for large high-throughput experiments in molecular biology, aims at an innovative contribution that enables sustainable and significant impact to the life sciences.