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J. Qi

dblp:45/5375 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2006
—ORCID · none

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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › sequence analysis › sequence comparison
alignment-free sequence comparison
0.112006
Ribosomal RNA as molecular barcodes: a simple correlation analysis without sequence alignment · Bioinform. 2006
Bioinformatics and computational biology
DNA barcoding
0.112006
Ribosomal RNA as molecular barcodes: a simple correlation analysis without sequence alignment · Bioinform. 2006
Bioinformatics and computational biology › RNA biology
ribosomal RNA
0.112006
Ribosomal RNA as molecular barcodes: a simple correlation analysis without sequence alignment · Bioinform. 2006

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

composition vector correlation analysis · 0.1
YearPublicationVenuePosition
2006 Ribosomal RNA as molecular barcodes: a simple correlation analysis without sequence alignment
abstract
MOTIVATION: We explored the feasibility of using unaligned rRNA gene sequences as DNA barcodes, based on correlation analysis of composition vectors (CVs) derived from nucleotide strings. We tested this method with seven rRNA (including 12, 16, 18, 26 and 28S) datasets from a wide variety of organisms (from archaea to tetrapods) at taxonomic levels ranging from class to species. RESULT: Our results indicate that grouping of taxa based on CV analysis is always in good agreement with the phylogenetic trees generated by traditional approaches, although in some cases the relationships among the higher systemic groups may differ. The effectiveness of our analysis might be related to the length and divergence among sequences in a dataset. Nevertheless, the correct grouping of sequences and accurate assignment of unknown taxa make our analysis a reliable and convenient approach in analyzing unaligned sequence datasets of various rRNAs for barcoding purposes. AVAILABILITY: The newly designed software (CVTree 1.0) is publicly available at the Composition Vector Tree (CVTree) web server http://cvtree.cbi.pku.edu.cn.
Ka Hou Chu, C. P. Li, J. Qi
Bioinform.3