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A. R. Galper

dblp:17/4336 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1991
—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%
Artificial intelligence
1 paper
Knowledge representation and reasoning · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Knowledge representation and reasoning › semantic representation
frame-based representation
0.011991
Knowledge-based simulation of DNA metabolism: prediction of enzyme action · Comput. Appl. Biosci. 1991
Knowledge, reasoning and agents › Knowledge representation and reasoning › knowledge-based systems › rule-based systems
production rule system
0.011991
Knowledge-based simulation of DNA metabolism: prediction of enzyme action · Comput. Appl. Biosci. 1991

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

truth maintenance system · 0.0production rules · 0.0frame-based representation · 0.0
YearPublicationVenuePosition
1991 Knowledge-based simulation of DNA metabolism: prediction of enzyme action
abstract
We have developed a knowledge-based simulation of DNA metabolism that accurately predicts the actions of enzymes on DNA under a large number of environmental conditions. Previous simulations of enzyme systems rely predominantly on mathematical models. We use a frame-based representation to model enzymes, substrates and conditions. Interactions between these objects are expressed using production rules and an underlying truth maintenance system. The system performs rapid inference and can explain its reasoning. A graphical interface provides access to all elements of the simulation, including object representations and explanation graphs. Predicting enzyme action is the first step in the development of a large knowledge base to envision the metabolic pathways of DNA replication and repair.
Douglas L. Brutlag, A. R. Galper, D. H. Millis
Comput. Appl. Biosci.2