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Thomas Yan

dblp:24/2845 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2005
—ORCID · none

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

Theory of computation · 1 · 1 first-authorApplied, 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 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
biological database
0.112005
Querying and computing with BioCyc databases · Bioinform. 2005
Bioinformatics and computational biology › biological database
pathway database
0.112005
Querying and computing with BioCyc databases · Bioinform. 2005

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

SQL · 0.1API access · 0.1
YearPublicationVenuePosition
2005 Querying and computing with BioCyc databases
abstract
Summary: We describe multiple methods for accessing and querying the complex and integrated cellular data in the BioCyc family of databases: access through multiple file formats, access through Application Program Interfaces (APIs) for LISP, Perl and Java, and SQL access through the BioWarehouse relational database. Availability: The Pathway Tools software and 20 BioCyc DBs in Tiers 1 and 2 are freely available to academic users; fees apply to some types of commercial use. For download instructions see http://BioCyc.org/download.shtml Supplementary information: For more details on programmatic access to BioCyc DBs, see http://bioinformatics.ai.sri.com/ptools/ptools-resources.html Contact: [email protected]
Markus Krummenacker, Suzanne M. Paley, Lukas A. Mueller, Thomas Yan, Peter D. Karp
Bioinform.4
1998 The Geobucket Data Structure for Polynomials
abstract
Thegeobucketdata structure is a suitable intermediate representation of polynomials for performing large numbers of polynomial additions in the face of interspersed lead-term extractions. A sum involvingNterms has worst-case running timeO(N log N), matching or surpassing the performance of lists and binomial heaps. This makes the geobucket a good choice for performing reductions in Gröbner basis computations.
Thomas Yan
J. Symb. Comput.1