1. Molecular Biology for Computer Scientists, Lawrence Hunter. 2. The Computational Linguistics of Biological Sequences, David B. Searls. 3. Neural Networks, Adaptive Optimisation, and RNA Secondary Structure Prediction, Evan W Steeg. 4. Predicting Protein Structural Features With Artificial Neural Networks, Stephen R. Holbrook, et al; 5. Developing Hierarchical Representations for Protein Structures: An Incremental Approach, Xiru Zhang and David Waltz. 6. Integrating AI with Sequence Analysis, Richard H. Lathrop, et al. 7. Planning to Learn about Protein Structure, Lawrence Hunter. 8. A Qualitative Biochemistry and its Application to the Regulation of the Tryptophan Operon, Peter D. Karp. 9. Identification of Qualitatively Feasible Metabolic Pathways, Michael L Mavrovouniotis. 10. Knowledge-Based Simulation of DNA Metabolism: Prediction of Action and Envisionment of Pathways, Adam R. Galper, et al. 11. An AI Approach to the Interpretation of the NMR Spectra of Proteins, Peter Edwards, et al. 12. Molecular Scene Analysis: Crystal Structure Determination Through Imagery, Janice I. Glasgow, et al. Afterword: The Anti-Expert System-Thirteen Hypotheses an AI Program Should Have Seen Through, Joshua Lederberg.