Demo Data from EDBT 2026 / reviewers in the wild / expert
Johannes Dröge
dblp:123/1735
· DBLP profile ↗
2ranked-venue papers
2as first author
0since 2021 · last 2015
0000-0002-6752-2204ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2 · 2 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
1 paper |
Bioinformatics and computational biology · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
metagenomics |
0.2 | 1 | 2015 | Taxator-tk: precise taxonomic assignment of metagenomes by fast approximation of evolutionary neighborhoods · Bioinform. 2015 |
Bioinformatics and computational biology › computational microbiology › microbiome analysis
microbial community profiling |
0.2 | 1 | 2015 | Taxator-tk: precise taxonomic assignment of metagenomes by fast approximation of evolutionary neighborhoods · Bioinform. 2015 |
Bioinformatics and computational biology › metagenomics
taxonomic classification |
0.2 | 1 | 2015 | Taxator-tk: precise taxonomic assignment of metagenomes by fast approximation of evolutionary neighborhoods · Bioinform. 2015 |
Methods — techniques the papers use, named apart from their topics
sequence similarity · 0.2parallelization · 0.2approximate evolutionary neighbor search · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Taxator-tk: precise taxonomic assignment of metagenomes by fast approximation of evolutionary neighborhoodsabstractMOTIVATION: Metagenomics characterizes microbial communities by random shotgun sequencing of DNA isolated directly from an environment of interest. An essential step in computational metagenome analysis is taxonomic sequence assignment, which allows identifying the sequenced community members and reconstructing taxonomic bins with sequence data for the individual taxa. For the massive datasets generated by next-generation sequencing technologies, this cannot be performed with de-novo phylogenetic inference methods. We describe an algorithm and the accompanying software, taxator-tk, which performs taxonomic sequence assignment by fast approximate determination of evolutionary neighbors from sequence similarities. RESULTS: Taxator-tk was precise in its taxonomic assignment across all ranks and taxa for a range of evolutionary distances and for short as well as for long sequences. In addition to the taxonomic binning of metagenomes, it is well suited for profiling microbial communities from metagenome samples because it identifies bacterial, archaeal and eukaryotic community members without being affected by varying primer binding strengths, as in marker gene amplification, or copy number variations of marker genes across different taxa. Taxator-tk has an efficient, parallelized implementation that allows the assignment of 6 Gb of sequence data per day on a standard multiprocessor system with 10 CPU cores and microbial RefSeq as the genomic reference data. Johannes Dröge, I. Gregor, Alice C. McHardy |
Bioinform. | 1 |
| 2012 | Taxonomic binning of metagenome samples generated by next-generation sequencing technologiesabstractMetagenome research uses random shotgun sequencing of microbial community DNA to study the genetic sequences of its members without cultivation. This development has been strongly supported by improvements in sequencing technologies, which have rendered sequencing cheaper than before. As a consequence, downstream computational analysis of metagenome sequence samples is now faced with large amounts of complex data. One of the essential steps in metagenome analysis is reconstruction of draft genomes for populations of a community or of draft 'pan-genomes' for higher level clades. 'Taxonomic binning' corresponds to the process of assigning a taxonomic identifier to sequence fragments, based on information such as sequence similarity, sequence composition or read coverage. This is used for draft genome reconstruction, if sequencing coverage is insufficient for reconstruction based on assembly information alone. Subsequent functional and metabolic annotation of draft genomes allows a genome-level analysis of novel uncultured microbial species and even inference of their cultivation requirements. Johannes Dröge, Alice C. McHardy |
Briefings Bioinform. | 1 |