Henrik Flyvbjerg

dblp:58/3183 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2015
0000-0002-1691-9367ORCID · verified

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

Artificial intelligence and machine learning · 1Applied, interdisciplinary, general and emerging computing · 1

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 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › sequence analysis › sequence assembly
paired-read assembly
0.212015
Error filtering, pair assembly and error correction for next-generation sequencing reads · Bioinform. 2015
Bioinformatics and computational biology
sequence analysis
0.212015
Error filtering, pair assembly and error correction for next-generation sequencing reads · Bioinform. 2015
Bioinformatics and computational biology › sequence analysis
sequencing error correction
0.212015
Error filtering, pair assembly and error correction for next-generation sequencing reads · Bioinform. 2015
Bioinformatics and computational biology › sequence analysis › sequencing data processing
sequencing quality control
0.112015
Error filtering, pair assembly and error correction for next-generation sequencing reads · Bioinform. 2015

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

k-mer based error correction · 0.2error filtering · 0.2
YearPublicationVenuePosition
2015 Error filtering, pair assembly and error correction for next-generation sequencing reads
abstract
MOTIVATION: Next-generation sequencing produces vast amounts of data with errors that are difficult to distinguish from true biological variation when coverage is low. RESULTS: We demonstrate large reductions in error frequencies, especially for high-error-rate reads, by three independent means: (i) filtering reads according to their expected number of errors, (ii) assembling overlapping read pairs and (iii) for amplicon reads, by exploiting unique sequence abundances to perform error correction. We also show that most published paired read assemblers calculate incorrect posterior quality scores. AVAILABILITY AND IMPLEMENTATION: These methods are implemented in the USEARCH package. Binaries are freely available at http://drive5.com/usearch. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Robert C. Edgar, Henrik Flyvbjerg
Bioinform.2
1998 Mining multi-channel EEG for its information content: an ANN-based method for a brain-computer interface
Björn O. Peters, Gert Pfurtscheller, Henrik Flyvbjerg
Neural Networks3