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Yanbo Ye

dblp:138/5753 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2013
—ORCID · none

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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
comparative genomics
0.212013
BlastGraph: a comparative genomics tool based on BLAST and graph algorithms · Bioinform. 2013
Bioinformatics and computational biology › comparative genomics
genome comparison
0.212013
BlastGraph: a comparative genomics tool based on BLAST and graph algorithms · Bioinform. 2013
Bioinformatics and computational biology › sequence alignment › heuristic alignment
BLAST
0.012013
BlastGraph: a comparative genomics tool based on BLAST and graph algorithms · Bioinform. 2013
Bioinformatics and computational biology
sequence analysis
0.012013
BlastGraph: a comparative genomics tool based on BLAST and graph algorithms · Bioinform. 2013

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

graph clustering · 0.2BLAST · 0.2
YearPublicationVenuePosition
2013 BlastGraph: a comparative genomics tool based on BLAST and graph algorithms
abstract
UNLABELLED: BlastGraph is an interactive Java program for comparative genome analysis based on Basic Local Alignment Search Tool (BLAST), graph clustering and data visualization. The software generates clusters of sequences of multiple genomes from all-to-all BLAST results and visualizes the results in graph plots together with related information such as sequence features, gene conservation and similarity relationships. Pruning algorithms are used to reduce results to more meaningful subclusters. Subsequent analyses can then be conducted based on the predicted clusters, including gene content, genome phylogenetics and gene gain and loss. AVAILABILITY AND IMPLEMENTATION: https://github.com/bigwiv/BlastGraph.
Yanbo Ye, Lei Wen, Simon Rayner
Bioinform.1