Demo Data from VLDB 2026 / reviewers in the wild / expert
Udo Stenzel
dblp:42/6000
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 3
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% | |
| Theoretical computer science
1 paper |
Algorithms and data structures · 100% |
Topics — the 7 heaviest of 9, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › single-cell analysis › single-cell data preprocessing
demultiplexing |
0.2 | 1 | 2015 | deML: robust demultiplexing of Illumina sequences using a likelihood-based approach · Bioinform. 2015 |
Bioinformatics and computational biology › sequence analysis
base calling |
0.2 | 1 | 2013 | freeIbis: an efficient basecaller with calibrated quality scores for Illumina sequencers · Bioinform. 2013 |
Bioinformatics and computational biology
sequence alignment |
0.1 | 1 | 2008 | PatMaN: rapid alignment of short sequences to large databases · Bioinform. 2008 |
Bioinformatics and computational biology
sequence analysis |
0.1 | 1 | 2008 | PatMaN: rapid alignment of short sequences to large databases · Bioinform. 2008 |
Bioinformatics and computational biology › genomics
genotyping |
0.0 | 1 | 2013 | freeIbis: an efficient basecaller with calibrated quality scores for Illumina sequencers · Bioinform. 2013 |
Algorithms and data structures › sequence algorithms › string algorithms › string matching
approximate string matching |
0.0 | 1 | 2008 | PatMaN: rapid alignment of short sequences to large databases · Bioinform. 2008 |
Algorithms and data structures › sequence algorithms › string algorithms
string matching |
0.0 | 1 | 2008 | PatMaN: rapid alignment of short sequences to large databases · Bioinform. 2008 |
Methods — techniques the papers use, named apart from their topics
maximum likelihood · 0.2multiclass support vector machine · 0.2non-deterministic automata matching · 0.2keyword tree · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | deML: robust demultiplexing of Illumina sequences using a likelihood-based approachabstractMOTIVATION: Pooling multiple samples increases the efficiency and lowers the cost of DNA sequencing. One approach to multiplexing is to use short DNA indices to uniquely identify each sample. After sequencing, reads must be assigned in silico to the sample of origin, a process referred to as demultiplexing. Demultiplexing software typically identifies the sample of origin using a fixed number of mismatches between the read index and a reference index set. This approach may fail or misassign reads when the sequencing quality of the indices is poor. RESULTS: We introduce deML, a maximum likelihood algorithm that demultiplexes Illumina sequences. deML computes the likelihood of an observed index sequence being derived from a specified sample. A quality score which reflects the probability of the assignment being correct is generated for each read. Using these quality scores, even very problematic datasets can be demultiplexed and an error threshold can be set. AVAILABILITY AND IMPLEMENTATION: deML is freely available for use under the GPL (http://bioinf.eva.mpg.de/deml/). Gabriel Renaud, Udo Stenzel, Tomislav Maricic, Victor Wiebe, Janet Kelso |
Bioinform. | 2 |
| 2013 | freeIbis: an efficient basecaller with calibrated quality scores for Illumina sequencersabstractMOTIVATION: The conversion of the raw intensities obtained from next-generation sequencing platforms into nucleotide sequences with well-calibrated quality scores is a critical step in the generation of good sequence data. While recent model-based approaches can yield highly accurate calls, they require a substantial amount of processing time and/or computational resources. We previously introduced Ibis, a fast and accurate basecaller for the Illumina platform. We have continued active development of Ibis to take into account developments in the Illumina technology, as well as to make Ibis fully open source. RESULTS: We introduce here freeIbis, which offers significant improvements in sequence accuracy owing to the use of a novel multiclass support vector machine (SVM) algorithm. Sequence quality scores are now calibrated based on empirically observed scores, thus providing a high correlation to their respective error rates. These improvements result in downstream advantages including improved genotyping accuracy. AVAILABILITY AND IMPLEMENTATION: FreeIbis is freely available for use under the GPL (http://bioinf.eva.mpg.de/freeibis/). It requires a Python interpreter and a C++ compiler. Tailored versions of LIBOCAS and LIBLINEAR are distributed along with the package. Gabriel Renaud, Martin Kircher, Udo Stenzel, Janet Kelso |
Bioinform. | 3 |
| 2008 | PatMaN: rapid alignment of short sequences to large databasesabstractUNLABELLED: We present a tool suited for searching for many short nucleotide sequences in large databases, allowing for a predefined number of gaps and mismatches. The commandline-driven program implements a non-deterministic automata matching algorithm on a keyword tree of the search strings. Both queries with and without ambiguity codes can be searched. Search time is short for perfect matches, and retrieval time rises exponentially with the number of edits allowed. AVAILABILITY: The C++ source code for PatMaN is distributed under the GNU General Public License and has been tested on the GNU/Linux operating system. It is available from http://bioinf.eva.mpg.de/patman. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Kay Prüfer, Udo Stenzel, Michael Dannemann, Richard E. Green, Michael Lachmann, Janet Kelso |
Bioinform. | 2 |