Abstract
Methods for analyzing the amino-acid sequence of a protein for the purposes of predicting its three-dimensional structure were systematically analyzed using knowledge engineering techniques. The resulting entities (data) and relations (processing methods and constraints) have been represented within a generalized dependency network consisting of 29 nodes and over 100 links. It is argued that such a representation meets the requirements of knowledge-based systems in molecular biology. This network is used as the architecture for a prototype knowledge-based system that simulates logically the processes used in protein structure prediction. Although developed specifically for applications in protein structure prediction, the network architecture provides a strategy for tackling the general problem of orchestrating and integrating the diverse sources of knowledge that are characteristic of many areas of science.
| Original language | English |
|---|---|
| Pages (from-to) | 94-107 |
| Number of pages | 14 |
| Journal | Journal of Molecular Graphics |
| Volume | 8 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - Jun 1990 |
Keywords
- Amino Acid Sequence
- Artificial Intelligence
- Protein Conformation
- Proteins
- Tryptophan Synthase