Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Elaine Yu

dblp:02/2074 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2003
—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 · 67% Medical and health informatics · 33%

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

TopicWeightPapersLastEvidence papers
Medical and health informatics
clinical informatics
0.012003
An XML message broker framework for exchange and integration of microarray data · Bioinform. 2003
Bioinformatics and computational biology › data integration
microarray data integration
0.012003
An XML message broker framework for exchange and integration of microarray data · Bioinform. 2003
Bioinformatics and computational biology › biological database
microarray data management
0.012003
An XML message broker framework for exchange and integration of microarray data · Bioinform. 2003

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

XML message broker · 0.0MAGE-ML · 0.0
YearPublicationVenuePosition
2003 An XML message broker framework for exchange and integration of microarray data
abstract
MOTIVATION: Microarrays are an important research tool for the advancement of basic biological sciences. However this technology has yet to be integrated with clinical decision making. We have implemented an information framework based on the Microarray Gene Expression Markup Language (MAGE-ML) specification. We are using this framework to develop a test-bed integrated database application to identify genomic and imaging markers for diagnosis of breast cancer. RESULTS: We developed extensible software architecture for retrieving data from different microarray databases using MAGE-ML and for combining microarray data with breast cancer image analysis and clinical data for correlation studies. The framework we developed will provide the necessary data integration to move microarray research from basic biological sciences to clinical applications. AVAILABILITY: Open source software will be available from SourceForge (http://sourceforge.net/projects/microsoap/).
Donny Tjandra, Stephen T. C. Wong, Weimin Shen, Brian Pulliam, Elaine Yu, Laura Esserman
Bioinform.5