I have an interactive database of 67 gene levels in multiple specimens ~100. These genes were chosen for probable activity. Many of the genes are interactive with others. I am trying to determine the best group of genes that correlate with each individual gene. Using various platforms (predictor screening utility, boosted tree/forest in partition, response screening in modeling, and screening in modeling), I get a similar hierarchy of genes, which make biological sense. However, using response screening in fit model, I get a very different hierarchy, which makes much less biological sense. Any ideas why the response screening in fit model is so different.