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Demo Data from EDBT 2026 / reviewers in the wild / expert

Sheree Yau

dblp:46/9984 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2011
0000-0003-1878-132XORCID · reported

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 annotation		 0.112011
Simple high-throughput annotation pipeline (SHAP) · Bioinform. 2011
Bioinformatics and computational biology › sequence analysis
DNA sequence analysis		 0.012011
Simple high-throughput annotation pipeline (SHAP) · Bioinform. 2011
Bioinformatics and computational biology
genomics		 0.012011
Simple high-throughput annotation pipeline (SHAP) · Bioinform. 2011

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

relational database · 0.1grid computing · 0.1full-text search · 0.1
YearPublicationVenuePosition
2011 Simple high-throughput annotation pipeline (SHAP)
abstract
SUMMARY: SHAP (simple high-throughput annotation pipeline) is a lightweight and scalable sequence annotation pipeline capable of supporting research efforts that generate or utilize large volumes of DNA sequence data. The software provides Grid capable analysis, relational storage and Web-based full-text searching of annotation results. Implemented in Java, SHAP recognizes the limited resources of many smaller research groups. AVAILABILITY: Source code is freely available under GPLv3 at https://sourceforge.net/projects/shap. CONTACT: [email protected]; [email protected].
Matthew Z. DeMaere, Federico M. Lauro, Torsten Thomas, Sheree Yau, Ricardo Cavicchioli
 Bioinform.4