Seminar
Grace Shieh
A Machine Learning Approach to Infer
Genetic Networks
Inferring genetic interactions is of interest since it sheds light on important biochemical pathways. From a group of experiments-confirmed genetic interactions, we observed that paired gene expression curves of transcriptional compensatory interactions often were complementary (anti-similar) whereas those of transcriptional diminished interactions looked similar. This motivated us to develop a pattern recognition approach (called PARE) to infer genetic networks from time course microarray gene expression data (MGED).
