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Meiyang Liu

dblp:292/9663 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2021
—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%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Parallel and multicore computing · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › sequence analysis
sequencing data analysis
0.512021
RabbitQC: high-speed scalable quality control for sequencing data · Bioinform. 2021
Parallel and multicore computing › thread-level parallelism
multi-threaded implementation
0.112021
RabbitQC: high-speed scalable quality control for sequencing data · Bioinform. 2021
Parallel and multicore computing
parallel programming models
0.112021
RabbitQC: high-speed scalable quality control for sequencing data · Bioinform. 2021

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

vectorization · 1.0multithreading · 1.0
YearPublicationVenuePosition
2021 RabbitQC: high-speed scalable quality control for sequencing data
abstract
MOTIVATION: Modern sequencing technologies continue to revolutionize many areas of biology and medicine. Since the generated datasets are error-prone, downstream applications usually require quality control methods to pre-process FASTQ files. However, existing tools for this task are currently not able to fully exploit the capabilities of computing platforms leading to slow runtimes. RESULTS: We present RabbitQC, an extremely fast integrated quality control tool for FASTQ files, which can take full advantage of modern hardware. It includes a variety of operations and supports different sequencing technologies (Illumina, Oxford Nanopore and PacBio). RabbitQC achieves speedups between one and two orders-of-magnitude compared to other state-of-the-art tools. AVAILABILITY AND IMPLEMENTATION: C++ sources and binaries are available at https://github.com/ZekunYin/RabbitQC. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Zekun Yin, Hao Zhang 0142, Meiyang Liu, Honglei Song, Haidong Lan, Yanjie Wei, Beifang Niu, Bertil Schmidt
Bioinform.3