Bianca K. Stöcker

dblp:185/8395 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 2019
0000-0001-5263-2358ORCID · corroborated

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

Databases, data management, data science and information retrieval · 1 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 1 · 1 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 · 50% Computational science and engineering · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational science and engineering
error model
0.212016
SimLoRD: Simulation of Long Read Data · Bioinform. 2016
Bioinformatics and computational biology
sequencing simulation
0.212016
SimLoRD: Simulation of Long Read Data · Bioinform. 2016

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

error modeling · 0.2
YearPublicationVenuePosition
2019 Protein Complex Similarity Based on Weisfeiler-Lehman Labeling
Bianca K. Stöcker, Till Schäfer, Petra Mutzel, Johannes Köster, Nils M. Kriege, Sven Rahmann
SISAP1
2016 SimLoRD: Simulation of Long Read Data
abstract
MOTIVATION: Third generation sequencing methods provide longer reads than second generation methods and have distinct error characteristics. While there exist many read simulators for second generation data, there is a very limited choice for third generation data. RESULTS: We analyzed public data from Pacific Biosciences (PacBio) SMRT sequencing, developed an error model and implemented it in a new read simulator called SimLoRD. It offers options to choose the read length distribution and to model error probabilities depending on the number of passes through the sequencer. The new error model makes SimLoRD the most realistic SMRT read simulator available. AVAILABILITY AND IMPLEMENTATION: SimLoRD is available open source at http://bitbucket.org/genomeinformatics/simlord/ and installable via Bioconda (http://bioconda.github.io). CONTACT: [email protected] or [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Bianca K. Stöcker, Johannes Köster, Sven Rahmann
Bioinform.1