Demo Data from EDBT 2026 / reviewers in the wild / expert
Rolf Hilker
dblp:119/6484
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › sequence analysis › read mapping
read mapping visualization |
0.4 | 2 | 2016 | 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 |
0.1 | 1 | 2012 | UniMoG - a unifying framework for genomic distance calculation and sorting based on DCJ · Bioinform. 2012 |
Bioinformatics and computational biology › comparative genomics
genome rearrangement |
0.1 | 1 | 2012 | 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 |
0.1 | 1 | 2016 | ReadXplorer 2 - detailed read mapping analysis and visualization from one single source · Bioinform. 2016 |
Bioinformatics and computational biology › gene expression analysis
differential expression analysis |
0.1 | 1 | 2014 | ReadXplorer - visualization and analysis of mapped sequences · Bioinform. 2014 |
Bioinformatics and computational biology
transcriptomics |
0.1 | 1 | 2014 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | ReadXplorer 2 - detailed read mapping analysis and visualization from one single sourceabstractMOTIVATION: 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 sequencesabstractMOTIVATION: 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 DCJabstractSUMMARY: 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 |