Demo Data from EDBT 2026 / reviewers in the wild / expert
Brian Pulliam
dblp:86/609
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Medical and health informatics
clinical informatics |
0.0 | 1 | 2003 | An XML message broker framework for exchange and integration of microarray data · Bioinform. 2003 |
Bioinformatics and computational biology › data integration
microarray data integration |
0.0 | 1 | 2003 | An XML message broker framework for exchange and integration of microarray data · Bioinform. 2003 |
Bioinformatics and computational biology › biological database
microarray data management |
0.0 | 1 | 2003 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2003 | An XML message broker framework for exchange and integration of microarray dataabstractMOTIVATION: 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. | 4 |