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Gene regulatory networks capture interactions between genes and other cell substances, resulting in various models for the fundamental biological process of transcription and translation. The expression levels of the genes are typically measured as mRNA concentration in micro-array experiments. In a so-called genetic perturbation experiment, small perturbations are applied to equilibrium states and...
Artificial microbial ecosystems have been increasingly used to understand principles of ecology. These systems offer unique capabilities to mimic a variety of ecological interactions that otherwise would be difficult to study experimentally in a reasonable period of time. However, the elucidation of the genetic bases for these interactions remains a daunting challenge. To address this issue, we have...
During the last years, the amount of genetic data available has increased rapidly which creates the demand for advanced techniques for their interpretation. In the following, we present an approach of applying communication theory for biological sequence analysis. We use an analogy to frame synchronization to gain more insights into transcription, the step of copying a gene into messenger RNA (mRNA)...
Microarray techniques provide new methods to find coregulated genes based on their coexpression profiles. Under the assumption that coregulated genes share cis acting regulatory elements, it is important to investigate the upstream sequences controlling the transcription of these genes. A modified Gibbs sampling algorithm with background interpolated Markov model (IMM) has been developed to detect...
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