MODELING AND ARTIFICIAL INTELLIGENCE APPROACHES TO ENZYME SYSTEMS.

David Garfinkel, Casimir A. Kulikowski, Von Wun Soo, Julio Maclay, Murray J. Achs

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

These include performance of serious modeling on laboratory microcomputers, e. g. IBM PCs such as fitting models to kinetic data with linear or nonlinear regression and graphical assistance; use of PC to rapidly build multienzyme models of metabolic systems, which have previously taken much longer on large computers; use of PCs to build data bases used for modeling; extraction of information from models by sensitivity analysis; and use of the preceding to design experiments. Artificial intelligence techniques permit critiquing and evaluating the data, experiments, and hypotheses being modeled. Much of the modeling process can be stated within the framework of expert systems (now becoming available on microcomputers) using sets of rules for fitting and evaluating models and designing further experiments. Such expert systems can supervise calculations in addition to performing reasoning.

Original languageEnglish (US)
Pages (from-to)92
Number of pages1
JournalAnnals of Biomedical Engineering
Volume14
Issue number1
StatePublished - 1986
Externally publishedYes
EventBiomed Eng Soc (BES) 1986 Symp - St Louis, MO, USA
Duration: Apr 13 1986Apr 18 1986

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering

Fingerprint

Dive into the research topics of 'MODELING AND ARTIFICIAL INTELLIGENCE APPROACHES TO ENZYME SYSTEMS.'. Together they form a unique fingerprint.

Cite this