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Zhiqun Xie

dblp:209/7671 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2017
0000-0001-7163-7242ORCID · reported

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

Applied, 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 · 100%

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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
genome annotation
0.312017
ISEScan: automated identification of insertion sequence elements in prokaryotic genomes · Bioinform. 2017
Bioinformatics and computational biology › genome annotation
transposable element annotation
0.312017
ISEScan: automated identification of insertion sequence elements in prokaryotic genomes · Bioinform. 2017

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

profile hidden markov model · 0.3
YearPublicationVenuePosition
2017 ISEScan: automated identification of insertion sequence elements in prokaryotic genomes
abstract
MOTIVATION: The insertion sequence (IS) elements are the smallest but most abundant autonomous transposable elements in prokaryotic genomes, which play a key role in prokaryotic genome organization and evolution. With the fast growing genomic data, it is becoming increasingly critical for biology researchers to be able to accurately and automatically annotate ISs in prokaryotic genome sequences. The available automatic IS annotation systems are either providing only incomplete IS annotation or relying on the availability of existing genome annotations. Here, we present a new IS elements annotation pipeline to address these issues. RESULTS: ISEScan is a highly sensitive software pipeline based on profile hidden Markov models constructed from manually curated IS elements. ISEScan performs better than existing IS annotation systems when tested on prokaryotic genomes with curated annotations of IS elements. Applying it to 2784 prokaryotic genomes, we report the global distribution of IS families across taxonomic clades in Archaea and Bacteria. AVAILABILITY AND IMPLEMENTATION: ISEScan is implemented in Python and released as an open source software at https://github.com/xiezhq/ISEScan. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Zhiqun Xie, Haixu Tang
Bioinform.1