Jens Keilwagen

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The plant-specific, B3 domain-containing transcription factor ABSCISIC ACID INSENSITIVE3 (ABI3) is an essential component of the regulatory network controlling the development and maturation of the Arabidopsis thaliana seed. Genome-wide chromatin immunoprecipitation (ChIP-chip), transcriptome analysis, quantitative reverse transcriptase-polymerase chain(More)
The transcription factor LEAFY COTYLEDON1 (LEC1) controls aspects of early embryogenesis and seed maturation in Arabidopsis thaliana. To identify components of the LEC1 regulon, transgenic plants were derived in which LEC1 expression was inducible by dexamethasone treatment. The cotyledon-like leaves and swollen root tips developed by these plants contained(More)
Transcription factors are a main component of gene regulation as they activate or repress gene expression by binding to specific binding sites in promoters. The de-novo discovery of transcription factor binding sites in target regions obtained by wet-lab experiments is a challenging problem in computational biology, which has not been fully solved yet.(More)
In this paper we introduce an extension of the Traveling Salesman Problem (TSP), which is motivated by an important application in bioinformatics. In contrast to the TSP the costs do not only depend on each pair of two nodes traversed in succession in a cycle but on each triple of nodes traversed in succession. This problem can be formulated as optimizing a(More)
Binding of transcription factors to DNA is one of the keystones of gene regulation. The existence of statistical dependencies between binding site positions is widely accepted, while their relevance for computational predictions has been debated. Building probabilistic models of binding sites that may capture dependencies is still challenging, since the(More)
Precision-recall (PR) and receiver operating characteristic (ROC) curves are valuable measures of classifier performance. Here, we present the R-package PRROC, which allows for computing and visualizing both PR and ROC curves. In contrast to available R-packages, PRROC allows for computing PR and ROC curves and areas under these curves for soft-labeled data(More)
For three decades, sequence logos are the de facto standard for the visualization of sequence motifs in biology and bioinformatics. Reasons for this success story are their simplicity and clarity. The number of inferred and published motifs grows with the number of data sets and motif extraction algorithms. Hence, it becomes more and more important to(More)
De novo motif discovery has been an important challenge of bioinformatics for the past two decades. Since the emergence of high-throughput techniques like ChIP-seq, ChIP-exo and protein-binding microarrays (PBMs), the focus of de novo motif discovery has shifted to runtime and accuracy on large data sets. For this purpose, specialized algorithms have been(More)
Jstacs is an object-oriented Java library for analysing and classifying sequence data, which emerged from the need for a standardized implementation of statistical models, learning principles, classifiers, and performance measures. In Jstacs, these components can be used, combined, and extended easily, which allows for a direct comparison of different(More)
Markov models have been proposed for the classification of DNA-motifs using generative approaches for parameter learning. Here, we propose to apply the discriminative paradigm for this problem and study two different priors to facilitate parameter estimation using the maximum supervised posterior. Considering seven sets of eukaryotic transcription factor(More)