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Benjamin P. Howden

dblp:417/1746 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · unresolved

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

Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

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 › genome assembly
bacterial genome assembly
0.912025
Autocycler: long-read consensus assembly for bacterial genomes · Bioinform. 2025
Bioinformatics and computational biology › sequence analysis › sequence assembly
genome assembly
0.912025
Autocycler: long-read consensus assembly for bacterial genomes · Bioinform. 2025
Bioinformatics and computational biology › sequence analysis › sequence assembly › genome assembly
long-read assembly
0.912025
Autocycler: long-read consensus assembly for bacterial genomes · Bioinform. 2025
Bioinformatics and computational biology › sequence analysis
long-read sequencing
0.312025
Autocycler: long-read consensus assembly for bacterial genomes · Bioinform. 2025

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

de bruijn graph · 0.9contig clustering · 0.9consensus variant selection · 0.9
YearPublicationVenuePosition
2025 Autocycler: long-read consensus assembly for bacterial genomes
abstract
MOTIVATION: Long-read sequencing enables complete bacterial genome assemblies, but individual assemblers are imperfect and often produce sequence-level and structural errors. Consensus assembly using Trycycler can improve accuracy, but its lack of automation limits scalability. There is a need for an automated method to generate high-quality consensus bacterial genome assemblies from long-read data. RESULTS: We present Autocycler, a command-line tool for generating accurate bacterial genome assemblies by combining multiple alternative long-read assemblies of the same genome. Without requiring user input, Autocycler builds a compacted De Bruijn graph from the input assemblies, clusters and filters contigs, trims overlaps, and resolves consensus sequences by selecting the most common variant at each locus. It also supports manual curation when desired, allowing users to refine assemblies in challenging or important cases. In our evaluation using Oxford Nanopore Technologies reads from five bacterial isolates, Autocycler outperformed individual assemblers, automated pipelines, and other consensus tools, producing assemblies with lower error rates and improved structural accuracy. AVAILABILITY AND IMPLEMENTATION: Autocycler is implemented in Rust, open-source, and freely available at github.com/rrwick/Autocycler. It runs on Linux and macOS and is extensively documented.
Ryan R. Wick, Benjamin P. Howden, Timothy P. Stinear
Bioinform.2