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Rolf Hilker

dblp:119/6484 · DBLP profile ↗
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3ranked-venue papers
3as first author
0since 2021 · last 2016
0000-0002-8576-7731ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 3 · 3 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
3 papers
Bioinformatics and computational biology · 100%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › sequence analysis › read mapping
read mapping visualization
0.422016
ReadXplorer 2 - detailed read mapping analysis and visualization from one single source · Bioinform. 2016
ReadXplorer - visualization and analysis of mapped sequences · Bioinform. 2014
Bioinformatics and computational biology › comparative genomics › genome comparison
genome distance estimation
0.112012
UniMoG - a unifying framework for genomic distance calculation and sorting based on DCJ · Bioinform. 2012
Bioinformatics and computational biology › comparative genomics
genome rearrangement
0.112012
UniMoG - a unifying framework for genomic distance calculation and sorting based on DCJ · Bioinform. 2012
Bioinformatics and computational biology › genomics › structural variation
genomic rearrangement detection
0.112016
ReadXplorer 2 - detailed read mapping analysis and visualization from one single source · Bioinform. 2016
Bioinformatics and computational biology › gene expression analysis
differential expression analysis
0.112014
ReadXplorer - visualization and analysis of mapped sequences · Bioinform. 2014
Bioinformatics and computational biology
transcriptomics
0.112014
ReadXplorer - visualization and analysis of mapped sequences · Bioinform. 2014

Methods — techniques the papers use, named apart from their topics

read mapping classification · 0.4correlation analysis · 0.2coverage analysis · 0.2double-cut-and-join model · 0.1
YearPublicationVenuePosition
2016 ReadXplorer 2 - detailed read mapping analysis and visualization from one single source
abstract
MOTIVATION: The vast amount of already available and currently generated read mapping data requires comprehensive visualization, and should benefit from bioinformatics tools offering a wide spectrum of analysis functionality from just one source. Appropriate handling of multiple mapped reads during mapping analyses remains an issue that demands improvement. RESULTS: The capabilities of the read mapping analysis and visualization tool ReadXplorer were vastly enhanced. Here, we present an even finer granulated read mapping classification, improving the level of detail for analyses and visualizations. The spectrum of automatic analysis functions has been broadened to include genome rearrangement detection as well as correlation analysis between two mapping data sets. Existing functions were refined and enhanced, namely the computation of differentially expressed genes, the read count and normalization analysis and the transcription start site detection. Additionally, ReadXplorer 2 features a highly improved support for large eukaryotic data sets and a command line version, enabling its integration into workflows. Finally, the new version is now able to display any kind of tabular results from other bioinformatics tools. AVAILABILITY AND IMPLEMENTATION: http://www.readxplorer.org CONTACT: [email protected] information: Supplementary data are available at Bioinformatics online.
Rolf Hilker, Kai Bernd Stadermann, Oliver Schwengers, Evgeny Anisiforov, Sebastian Jaenicke, Bernd Weisshaar, Tobias Zimmermann, Alexander Goesmann
Bioinform.1
2014 ReadXplorer - visualization and analysis of mapped sequences
abstract
MOTIVATION: Fast algorithms and well-arranged visualizations are required for the comprehensive analysis of the ever-growing size of genomic and transcriptomic next-generation sequencing data. RESULTS: ReadXplorer is a software offering straightforward visualization and extensive analysis functions for genomic and transcriptomic DNA sequences mapped on a reference. A unique specialty of ReadXplorer is the quality classification of the read mappings. It is incorporated in all analysis functions and displayed in ReadXplorer's various synchronized data viewers for (i) the reference sequence, its base coverage as (ii) normalizable plot and (iii) histogram, (iv) read alignments and (v) read pairs. ReadXplorer's analysis capability covers RNA secondary structure prediction, single nucleotide polymorphism and deletion-insertion polymorphism detection, genomic feature and general coverage analysis. Especially for RNA-Seq data, it offers differential gene expression analysis, transcription start site and operon detection as well as RPKM value and read count calculations. Furthermore, ReadXplorer can combine or superimpose coverage of different datasets. AVAILABILITY AND IMPLEMENTATION: ReadXplorer is available as open-source software at http://www.readxplorer.org along with a detailed manual.
Rolf Hilker, Kai Bernd Stadermann, Daniel Doppmeier, Jörn Kalinowski, Jens Stoye, Jasmin Straube, Jörn Winnebald, Alexander Goesmann
Bioinform.1
2012 UniMoG - a unifying framework for genomic distance calculation and sorting based on DCJ
abstract
SUMMARY: UniMoG is a software combining five genome rearrangement models: double cut and join (DCJ), restricted DCJ, Hannenhalli and Pevzner (HP), inversion and translocation. It can compute the pairwise genomic distances and a corresponding optimal sorting scenario for an arbitrary number of genomes. All five models can be unified through the DCJ model, thus the implementation is based on DCJ and, where reasonable, uses the most efficient existing algorithms for each distance and sorting problem. Both textual and graphical output is possible for visualizing the operations. AVAILABILITY AND IMPLEMENTATION: The software is available through the Bielefeld University Bioinformatics Web Server at http://bibiserv.techfak.uni-bielefeld.de/dcj with instructions and example data. CONTACT: [email protected].
Rolf Hilker, Corinna Sickinger, Christian N. S. Pedersen, Jens Stoye
Bioinform.1