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Christopher Dubay

dblp:74/2473 · DBLP profile ↗
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4ranked-venue papers
1as 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 · 4 · 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
2 papers
Bioinformatics and computational biology · 67% Medical and health informatics · 33%

Topics — the 1 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Medical and health informatics › biomedical data science
biomedical database querying
0.012003
BioQuery: An Object Framework for Building Queries to Biomedical Databases · Bioinform. 2003

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

web portal · 0.1plugin architecture · 0.0object framework · 0.0
YearPublicationVenuePosition
2008 MonkeySNP: a web portal for non-human primate single nucleotide polymorphisms
abstract
UNLABELLED: MonkeySNP is a web-based resource created by the Genetic Resource and Informatics Program at the Oregon National Primate Research Center to facilitate access to non-human primate (NHP) single nucleotide polymorphisms (SNP) data. MonkeySNP is a mirror of the NCBI dbSNP database and contains additional NHP subpopulation genotype data and visual genotype displays to support SNP review and selection. AVAILABILITY: http://monkeysnp.ohsu.edu/snp/ SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Samone Khouangsathiene, Carlo Pearson, Summer Street, Betsy Ferguson, Christopher Dubay
Bioinform.5
2005 Using co-occurrence network structure to extract synonymous gene and protein names from MEDLINE abstracts
abstract
BACKGROUND: Text-mining can assist biomedical researchers in reducing information overload by extracting useful knowledge from large collections of text. We developed a novel text-mining method based on analyzing the network structure created by symbol co-occurrences as a way to extend the capabilities of knowledge extraction. The method was applied to the task of automatic gene and protein name synonym extraction. RESULTS: Performance was measured on a test set consisting of about 50,000 abstracts from one year of MEDLINE. Synonyms retrieved from curated genomics databases were used as a gold standard. The system obtained a maximum F-score of 22.21% (23.18% precision and 21.36% recall), with high efficiency in the use of seed pairs. CONCLUSION: The method performs comparably with other studied methods, does not rely on sophisticated named-entity recognition, and requires little initial seed knowledge.
Aaron M. Cohen, William R. Hersh, Christopher Dubay, Kent A. Spackman
BMC Bioinform.3
2003 BioQuery: An Object Framework for Building Queries to Biomedical Databases
abstract
SUMMARY: BioQuery is an application that helps scientists automate database searches. Users can build and store queries to public biomedical databases, and receive periodic updates on the results of those queries when new data is available. The application is implemented on a portable object framework that can provide database-searching capability to other applications. This framework is easily extensible, allowing users to develop plug-ins that provide access to new databases. BioQuery thus provides end-users with a complete database searching interface and updating service, and gives developers a toolkit to provide database-searching capability to their applications. AVAILABILITY: Free to all users: http://www.bioquery.org.
James M. Brundege, Christopher Dubay
Bioinform.2
2002 Delivering bioinformatics training: bridging the gaps between computer science and biomedicine
Christopher Dubay, James M. Brundege, William R. Hersh, Kent A. Spackman
AMIA1