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Stephen Ethier

dblp:45/2264 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2008
—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 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › biological database
microarray data management
0.112008
KUTE-BASE: storing, downloading and exporting MIAME-compliant microarray experiments in minutes rather than hours · Bioinform. 2008
Bioinformatics and computational biology › biological database
microarray database
0.012008
KUTE-BASE: storing, downloading and exporting MIAME-compliant microarray experiments in minutes rather than hours · Bioinform. 2008

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

workflow automation · 0.1plugin development · 0.1
YearPublicationVenuePosition
2008 KUTE-BASE: storing, downloading and exporting MIAME-compliant microarray experiments in minutes rather than hours
abstract
MOTIVATION: The BioArray Software Environment (BASE) is a very popular MIAME-compliant, web-based microarray data repository. However in BASE, like in most other microarray data repositories, the experiment annotation and raw data uploading can be very timeconsuming, especially for large microarray experiments. RESULTS: We developed KUTE (Karmanos Universal daTabase for microarray Experiments), as a plug-in for BASE 2.0 that addresses these issues. KUTE provides an automatic experiment annotation feature and a completely redesigned data work-flow that dramatically reduce the human-computer interaction time. For instance, in BASE 2.0 a typical Affymetrix experiment involving 100 arrays required 4 h 30 min of user interaction time forexperiment annotation, and 45 min for data upload/download. In contrast, for the same experiment, KUTE required only 28 min of user interaction time for experiment annotation, and 3.3 min for data upload/download. AVAILABILITY: http://vortex.cs.wayne.edu/kute/index.html.
Sorin Draghici, Adi L. Tarca, Stephen Ethier, Roberto Romero
Bioinform.4