Regulatory networks: Linking microarray data to systems biology

Gene regulation and aging are intrinsically linked and these links often reach directly to transcription factors and their actions in gene regulation. However, it is very difficult to follow all the individual directions such factors can affect. Therefore, the opposite approach became more popular recently, i.e. observing the endpoints of all these actions. Microarrays are the preferred technology to monitor large-scale changes in transcripts across whole genomes. The trade-off for being able to survey whole genome transcriptomes is that the results are mere observations, which do not directly reveal the underlying mechanisms that represent the real link to transcription factors and their actions. Fortunately, a combination of knowledge mining (including but not restricted to literature mining) with genomics analyses can be harnessed to elucidate at least some of the regulatory networks orchestrating the transcriptional changes observed by microarray experiments. Thus, a considerable part of the functional system structure of cells and organisms can be revealed, which is a pivotal prerequisite for any meaningful systems biology approach towards aging related phenotypes.