Q:
I’ve been trying to apply the Loregic algorithm in other organisms in order to further validate the method, however I’m finding some inconsistencies that could be related to data manipulation (choosing datasets, merging and mean-centering samples).
Furthermore, I’ve also found those inconsistencies when trying to reproduce the analysis from yeast datasets provided in your publication (probably due to the same data manipulation issues described before).

Would you be able to provide a more in-depth protocol for using Loregic with multiple datasets (how you handled the data, for example) in order to improve the consistency of the method between labs?

A:
Yes, we normalized the yeast data. Here was how we preprocessed:

1) got time-series yeast cell cycle data (alpha, cdc15, cdc28) from
http://genome-www.stanford.edu/cellcycle/data/rawdata/combined.txt,
which were logarithm values.
2) standardized(2^(data)) s.t., each time point has mean=0, and sigma=1
3) binarized the standardized data using the function,
binarizeTimeSeries with ‘kmeans’ clustering in R package BoolNet.