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J. P. Massar

dblp:51/1959 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2008
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1Applied, interdisciplinary, general and emerging computing · 1 · 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
1 paper
Bioinformatics and computational biology · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › bioinformatics infrastructure
bioinformatic tool integration
0.012005
BioLingua: a programmable knowledge environment for biologists · Bioinform. 2005

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

symbolic programming · 0.1end-user programming · 0.1
YearPublicationVenuePosition
2008 The CACHE Study: Group Effects in Computer-supported Collaborative Analysis
Gregorio Convertino, Dorrit Billman, Peter Pirolli, J. P. Massar, Jeff Shrager
Comput. Support. Cooperative Work.4
2005 BioLingua: a programmable knowledge environment for biologists
abstract
UNLABELLED: BioLingua is an interactive, web-based programming environment that enables biologists to analyze biological systems by combining knowledge and data through direct end-user programming. BioLingua embeds a mature symbolic programming language in a frame-based knowledge environment, integrating genomic and pathway knowledge about a class of similar organisms. The BioLingua language provides interfaces to numerous state-of-the-art bioinformatic tools, making these available as an integrated package through the novel use of web-based programmability and an integrated Wiki-based community code and data store. The pilot instantiation of BioLingua, which has been developed in collaboration with several cyanobacteriologists, integrates knowledge about a subset of cyanobacteria with the Gene Ontology, KEGG and BioCyc knowledge bases. We introduce the BioLingua concept, architecture and language, and give several examples of its use in complex analyses. AVAILABILITY: Extensive documentation is available online at http://nostoc.stanford.edu/Docs/index.html CONTACT: [email protected]
J. P. Massar, Michael Travers, Jeff Elhai, Jeff Shrager
Bioinform.1