Commit abb4c96c authored by Maik Fröbe's avatar Maik Fröbe
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Update README.md

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The taxonomic analysis of metagenomic sequencing data has become important in many areas of life sciences. However, currently available software tools for that purpose either consume large amounts of RAM or yield an insufficient quality of the results. To identify and profile metagenomic sequences with high computational efficiency and a small user-definable memory footprint, we developed a k-mer based software named "kASA".
5. **Maik Fröbe**, Big Data Analytics
**Hidden Oversampling in Learning-to-Rank**
The machine learning approaches to solve the problem of ranking in search engines rely on vast amounts of training data. Those training datasets contain duplicated documents that are unexpected in subsequent machine learning algorithms. We investigate the impact of that "hidden oversampling" to the produced rankings of the search engine.
The machine learning approaches to solve the problem of ranking in search engines rely on vast amounts of training data. Those training datasets contain duplicated documents that are unexpected in subsequent machine learning algorithms. We investigate the impact of that "hidden oversampling" to the produced rankings of search engines.
6. **Annett Erkes**, Bioinformatik
**Bioinformatic analysis of TAL effectors in the Xanthomonas oryzae - rice interaction**
Diseases caused by plant-pathogenic Xanthomonas bacteria are a serious threat for many important crop plants including rice. Efficiently protecting plants from these pathogens requires a deeper understanding of infection strategies. Such infection strategies depend on a special class of effector
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