Chris Schleiermacher

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The repetitive structure of genomic DNA holds many secrets to be discovered. A systematic study of repetitive DNA on a genomic or inter-genomic scale requires extensive algorithmic support. The REPuter program described herein was designed to serve as a fundamental tool in such studies. Efficient and complete detection of various types of repeats is(More)
When a family of genes from closely related organisms is known, there is a certain change to extract the corresponding gene from the genome of another related organism. This can be done by polymerase chain reaction, provided that a pair of suitable primers can be designed. In contrast to primer design for a single, known target sequence, systematic primer(More)
SUMMARY Genalyzer is a software tool designed for the interactive visualization of sequence matches between DNA or protein sequences. It provides visualizations on different levels of granularity, from complete overviews via zoomed regions to alignments of particular matching substrings. Genalyzer can efficiently handle very large datasets, allowing to(More)
The repetitive structure of genomic DNA holds many secrets to be discovered. A systematic study of repetitive DNA on a genomic or inter-genomic scale requires extensive algorithmic support. The REPuter family of programs described herein was designed to serve as a fundamental tool in such studies. Efficient and complete detection of various types of repeats(More)
In this paper, an approach for efficiently extracting the repeating patterns in a biological sequence is proposed. A repeating pattern is a subsequence which appears more than once in a sequence, which is one of the most important features that can be used for revealing functional or evolutionary relationships in biological sequences. The algorithm does a(More)
GenAlyzer is a software tool designed for the interactive visualisation of sequence matches between DNA or Protein sequences. It provides visualisations on different levels of granularity, from complete overviews via zoomed regions to alignements of particular matching substrings. Gen can efficiently handle very large datasets, allowing to display tens of(More)
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