FACT--a framework for the functional interpretation of high-throughput experiments.
BACKGROUND
Interpreting the results of high-throughput experiments, such as those obtained from DNA-microarrays, is an often time-consuming task due to the high number of data-points that need to be analyzed in parallel. It is usually a matter of extensive testing and unknown beforehand, which of the possible approaches for the functional analysis will be the most informative.


RESULTS
To address this problem, we have developed the Flexible Annotation and Correlation Tool (FACT). FACT allows for detection of important patterns in large data sets by simplifying the integration of heterogeneous data sources and the subsequent application of different algorithms for statistical evaluation or visualization of the annotated data. The system is constantly extended to include additional annotation data and comparison methods.


CONCLUSIONS
FACT serves as a highly flexible framework for the explorative analysis of large genomic and proteomic result sets. The program can be used online; open source code and supplementary information are available at http://www.factweb.de.
Kokocinski
Felix
F
Molecular Genetics, Deutsches Krebsforschungszentrum, 69115 Heidelberg, Germany. F.Kokocinski@factweb.de
Delhomme
Nicolas
N
Wrobel
Gunnar
G
Hummerich
Lars
L
Toedt
Grischa
G
Lichter
Peter
P
D000465:Algorithms; D016000:Cluster Analysis; D003198:Computer Simulation; D001330:Electronic Data Processing / Q000379:methods*; D020869:Gene Expression Profiling; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010363:Pattern Recognition, Automated; D012984:Software; D018511:Systems Integration