Research Article
A Method for the Detection of Meaningful and Reproducible Group Signatures from Gene Expression Profiles
@INPROCEEDINGS{10.1007/978-3-642-32615-8_38, author={Louis Licamele and Lise Getoor}, title={A Method for the Detection of Meaningful and Reproducible Group Signatures from Gene Expression Profiles}, proceedings={Bio-Inspired Models of Network, Information, and Computing Systems. 5th International ICST Conference, BIONETICS 2010, Boston, USA, December 1-3, 2010, Revised Selected Papers}, proceedings_a={BIONETICS}, year={2012}, month={10}, keywords={gene expression analysis gene expression profiles drug discovery bioinformatics data mining}, doi={10.1007/978-3-642-32615-8_38} }- Louis Licamele
Lise Getoor
Year: 2012
A Method for the Detection of Meaningful and Reproducible Group Signatures from Gene Expression Profiles
BIONETICS
Springer
DOI: 10.1007/978-3-642-32615-8_38
Abstract
Gene expression microarrays are commonly used to detect the biological signature of a disease or to gain a better understanding of the underlying mechanism of how a group of drugs treat a specific disease. The outcome of such experiments, e.g., the signature, is a list of differentially expressed genes. Reproducibility across independent experiments remains a challenge. We are interested in creating a method that can detect the shared signature of a group of expression profiles, e.g., a group of samples from individuals with the same disease or a group of drugs that treat the same therapeutic indication. We have developed a novel Weighted Influence - Rank of Ranks (WIMRR) method, and we demonstrate its ability to produce both meaningful and reproducible group signatures.
