Rule-Based Reasoning
Report 77-07 Stanford -- KSL
Both tasks are concerned with the interpretation of large quantities of digitized signal data. The task of SU/X is to understand "continuous signal that is, signals which persist over time. The task of SU/P is to interpret protein x-ray crystallographic data. Some features of the design are: (1) incremental interpretation of data employing many different pattern-invoked sources of knowledge, (2) production rule representation of knowledge, includiR high level strategy knowledge, (3) "opportunistic" hypothesis formation using Dr,
Report 77 04 Application of Artificial Intelligence for Stanford Chemical Inference . Tom M. Mitchell Gretchen M.
The increasing popularity of 13 C techniques and the increasing bulk of available data have motivated us to develop a computer program which generates empirical 13 C NUR rules. A natural abundance 13 C NMR spectrum which is fully proton-- decoupled consists of a number of sharp peaks ccrresponding to the resonance frequencies in the applied magnetic field of the various types of carbon atoms present in the sample. A 13 C shift is the amount a peak position deviates from a reference peak of a standard compound usually tetramethylsilane (T1s). Methods for obtaining empirical rules which correlate 13 C shifts with local structural environments within a class of compounds are cited in the literature.
Submitted to MEDINF0.77
Almost one-half of the total cost of drugs spent in treating hospitalized patients is spend on antibiotics (1,2), and a significant part of this therapy is associated with serious misuse (2,3,4,5). One problem involves incorrect selection of a therapeutic regimen [4], while another involves the incorrect decision to administer any antibiotic (2,4,5). For example, one recent study concluded that one out of every four people in the United States was given penicillin during a recent year, and nearly 907. of these preL,criptions were oahccessary (6).
Knowledge-Based Simulation of DNA Metabolism: Prediction of Action and Envisionment of Pathways
Our understanding of any process can be measured by the extent to which a simulation we create mimics the real behavior of that process. Deviations of a simulation indicate either limitations or errors in our knowledge. In addition, these observed differences often suggest verifiable experimental hypotheses to extend our knowledge. The biochemical approach to understanding biological processes is essentially one of simulation. A biochemist typically prepares a cell-free extract that can mediate a well-described physiological process. The extract is then fractionated to purify the components that catalyze individual reactions.
The Computational Linguistics of Biological Sequences
Shortly after Watson and Crick's discovery of the structure of DNA, and at about the same time that the genetic code and the essential facts of gene expression were being elucidated, the field of linguistics was being similarly revolutionized by the work of Noam Chomsky [Chomsky, 1955, 1957, 1959, 1963, 1965]. Observing that a seemingly infinite variety of language was available to individual human beings based on clearly finite resources and experience, he proposed a formal representation of the rules or syntax of language, called generative grammar, that could provide finite--indeed, concise--characterizations of such infinite languages. Just as the breakthroughs in molecular biology in that era served to anchor genetic concepts in physical structures and opened up entirely novel experimental paradigms, so did Chomsky's insight serve to energize the field of linguistics, with putative correlates of cognitive processes that could for the first time be reasoned about 48 A