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Knut Reinert
Professor for Algorithmic Bioinformatics
Research Interests
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Articles (10)
Year:
2026
Year:
2026
Year:
2025
Year:
2025
Year:
2025
Year:
2025
Motivation The minimizer concept is a data structure for sequence sketching. The standard canonical minimizer selects a subset of k-mers from the given DNA sequence by comparing the forward and reverse k-mers in a window simultaneously according to a predefined selection scheme. It is widely employed by sequence analysis such as read mapping and assembly. k-mer density, k-mer repetitiveness (e.g. k-mer bias), and computational efficiency are three critical measurements for minimizer selection schemes. However, there exist trade-offs between kinds of minimizer variants. Generic, effective, and efficient are always the requirements for high-performance minimizer algorithms. Results We propose a simple minimizer operator as a refinement of the standard canonical minimizer. It takes only a few operations to compute. However, it can improve the k-mer repetitiveness, especially for the lexicographic order. It applies to other selection schemes of total orders (e.g. random orders). Moreover, it is computationally efficient and the density is close to that of the standard minimizer. The refined minimizer may benefit high-performance applications like binning and read mapping. Availability and implementation The source code of the benchmark in this work is available at the github repository https://github.com/xp3i4/mini_benchmark
Year:
2024
Year:
2021
Year:
2020
Year:
2020
Collaborators (4)
Jan Lisec
Federal Institute For Materials Research and Testing
Philipp Benner
Staff Scientist (Machine Learning) / Head of eScience Group
Federal Institute For Materials Research and Testing
Thilo Muth
Head of Division / Group Leader
Robert Koch Institute
Denise Kühnert
Head of Phylogenomics Unit
Robert Koch Institute
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