Abstract: Identifying cell cycle transcription factors (TFs) is important for understanding the transcriptional regulation of the cell cycle process which controls the growth and development of all organisms. Existing computational approaches for identifying cell cycle TFs are mainly based on methods with a fixed selection criterion. That is, the same criterion was applied to each TF to determine whether it is a cell cycle TF or not. Since the characteristic of each TF may be quite different, it is not suitable to use a fixed selection criterion in identifying cell cycle TFs. Instead of using a fixed selection criterion, we propose a method with variable selection criteria to identify cell cycle TFs in yeast by integrating the ChIP-chip and cell cycle gene expression data. Our method is shown to outperform five existing methods which used the same ChIP-chip dataset as we did. Fifteen cell cycle TFs were identified by our approach, 12 of which are known cell cycle TFs, while the remaining three (Hap4, Reb1 and Tye7) are novel cell cycle TFs. The biological significance of our predictions is shown by four lines of indirect evidence derived from the protein-protein interaction data, TF mutant data, ChIP-chip data and the results of the previous computational studies.