Computer Planning of Research in Organic Chemistry

  • W. Todd Wipke


Information processing is a very fundamental activity in research, probably more important than most of us realize. Research is begun based on previously established information and the product of research is also information. This output information results from experimental observations or combinations of and extrapolations from previous information. The majority of information processed, for example, by a chemist in research is non-numerical — symbols, words, relations, logical inference, etc.1 Numeric symbols and the common arithemetic operations are simply a small subset of what we need for information processing in research. It is only in the last decade that programming languages (eg. LISP) have been developed which enable one to easily manipulate symbolic representations within a computer, enabling one to begin applying computers to some of the more interesting non-numerical problems in science. The elegant work Buchanan presented at this meeting in structure elucidation is an example of what has been done in this area. In this paper I wish to focus on computer-assisted planning of research in organic chemistry in general. As illustrations, I will refer to recent applications in synthesis, mechanistic studies, and biogenesis.


Trans Form Planning Program Symbolic Representation Computer Planning Model Builder 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 1977

Authors and Affiliations

  • W. Todd Wipke
    • 1
  1. 1.Board of Studies in ChemistryUniveristy of CaliforniaSanta CruzUSA

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