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The automated annotation of data from high throughput sequencing and genomics experiments is a significant challenge for bioinformatics. Most current approaches rely on sequential pipelines of gene finding and gene function prediction methods that annotate a gene with information from different reference data sources. Each function prediction method(More)
Transcription factors (TFs) play a fundamental role in cellular regulation by binding to promoter regions of target genes (TGs) in order to control their gene expression. TF-TG networks are widely used as representations of regulatory mechanisms, e.g. for modeling the cellular response to input signals and perturbations. As the experimental identification(More)
Many large data compendia on context-specific high-throughput genomic and regulatory data have been made available by international research consortia such as ENCODE, TCGA, and Epigenomics Roadmap. The use of these resources is impaired by the sheer size of the available big data and big metadata. Many of these context-specific data can be modeled as data(More)
Metabolic processes, signal transduction, gene regulation, gene and protein expression in biological systems, all are controlled by means of networks. Several bioinformatics approaches have been introduced to infer networks from high-throughput data. But still, most networks are not known in detail for most biological systems. Thus, the question arises(More)
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