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Junpeng Fan

dblp:257/4286 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · unresolved

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

Applied, 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 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › sequence analysis › sequence assembly
genome assembly
0.412020
NextPolish: a fast and efficient genome polishing tool for long-read assembly · Bioinform. 2020
Bioinformatics and computational biology › sequence analysis › sequence assembly
genome polishing
0.412020
NextPolish: a fast and efficient genome polishing tool for long-read assembly · Bioinform. 2020
Bioinformatics and computational biology
genomics
0.412020
NextPolish: a fast and efficient genome polishing tool for long-read assembly · Bioinform. 2020
Bioinformatics and computational biology › sequence analysis
long-read sequencing
0.112020
NextPolish: a fast and efficient genome polishing tool for long-read assembly · Bioinform. 2020
Bioinformatics and computational biology › genomics
sequencing
0.112020
NextPolish: a fast and efficient genome polishing tool for long-read assembly · Bioinform. 2020

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

k-mer counting · 0.4error correction · 0.4
YearPublicationVenuePosition
2020 NextPolish: a fast and efficient genome polishing tool for long-read assembly
abstract
MOTIVATION: Although long-read sequencing technologies can produce genomes with long contiguity, they suffer from high error rates. Thus, we developed NextPolish, a tool that efficiently corrects sequence errors in genomes assembled with long reads. This new tool consists of two interlinked modules that are designed to score and count K-mers from high quality short reads, and to polish genome assemblies containing large numbers of base errors. RESULTS: When evaluated for the speed and efficiency using human and a plant (Arabidopsis thaliana) genomes, NextPolish outperformed Pilon by correcting sequence errors faster, and with a higher correction accuracy. AVAILABILITY AND IMPLEMENTATION: NextPolish is implemented in C and Python. The source code is available from https://github.com/Nextomics/NextPolish. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Junpeng Fan, Zongyi Sun, Shanlin Liu
Bioinform.2