Refine
H-BRS Bibliography
- yes (10) (remove)
Departments, institutes and facilities
- Institut für funktionale Gen-Analytik (IFGA) (10) (remove)
Document Type
- Article (5)
- Conference Object (5)
Year of publication
- 2008 (10) (remove)
Keywords
- Complement receptor 2/CD21 (2)
- shedding (2)
- Algorithms (1)
- Antiphospholipid syndrome (APS) (1)
- Autoantibody (1)
- B cell activation (1)
- Bcl-2 (1)
- Bicycle Simulator (1)
- Complement receptor 2 /CD21 (1)
- Computer Graphics (1)
Suprabasal BCL-2 Expression Does Not Sensitize to Chemically-induced Skin Cancer in Transgenic Mice
(2008)
The automated annotation of data from high throughput sequencing and genomics experiments is a significant challenge for bioinformatics. Most current approaches rely on sequential pipelines of gene finding and gene function prediction methods that annotate a gene with information from different reference data sources. Each function prediction method contributes evidence supporting a functional assignment. Such approaches generally ignore the links between the information in the reference datasets. These links, however, are valuable for assessing the plausibility of a function assignment and can be used to evaluate the confidence in a prediction. We are working towards a novel annotation system that uses the network of information supporting the function assignment to enrich the annotation process for use by expert curators and predicting the function of previously unannotated genes. In this paper we describe our success in the first stages of this development. We present the data integration steps that are needed to create the core database of integrated reference databases (UniProt, PFAM, PDB, GO and the pathway database Ara-Cyc) which has been established in the ONDEX data integration system. We also present a comparison between different methods for integration of GO terms as part of the function assignment pipeline and discuss the consequences of this analysis for improving the accuracy of gene function annotation. The methods and algorithms presented in this publication are an integral part of the ONDEX system which is freely available from http://ondex.sf.net/.
The objective of the FIVIS project is to develop a bicycle simulator which is able to simulate real life bicycle ride situations as a virtual scenario within an immersive environment. A sample test bicycle is mounted on a motion platform to enable a close to reality simulation of turns and balance situations. The visual field of the bike rider is enveloped within a multi-screen visualization environment which provides visual data relative to the motion and activity of the test bicycle. This implies the bike rider has to pedal and steer the bicycle as they would a traditional bicycle, while forward motion is recorded and processed to control the visualization. Furthermore, the platform is fed with real forces and accelerations that have been logged by a mobile data acquisition system during real bicycle test drives. Thus, using a feedback system makes the movements of the platform reflect the virtual environment and the reaction of the driver (e.g. steering angle, step rate).