Preface. 1. Grand challenges in computational biology (D.B. Searls). 2. A tutorial introduction to computation for biologists (S.L. Salzberg). 3. An introduction to biological sequence analysis (K.H. Fasman, S.L. Salzberg). 4. An introduction to hidden Markov models for biological sequences (A. Krogh). 5. Case-based reasoning driven gene annotation (G.C. Overton, J. Haas). 6. Classification-based molecular sequence analysis (D.J. States, W.C. Reisdorf, Jr.) 7. Computational gene prediction using neural networks and similarity search (Y. Xu, E.C. Uberbacher). 8. Modeling dependencies in pre-mRNA splicing signals (C.B. Burge). 9. Evolutionary approaches to computational biology (R.J. Parsons). 10. Decision trees and Markov chains for gene finding (S.L. Salzberg). 11. Statistical analysis of protein structures: using environmental features for multiple purposes (L. Wei, J.T. Chang, R.B. Altman). 12. Analysis and algorithms for protein sequence-structure alignment (R.H. Lathrop et al.). 13. THREADER: protein sequence threading by double dynamic programming (D. Jones). 14. From computer vision to protein structure and association (H.J. Wolfson, R. Nussinov). 15. Modeling biological data and structure with probabilistic networks (S. Kasif, A.L. Delcher). Appendix A: Software and databases for computational biology on the Internet. Appendix B: Suggestions for further reading in computational biology.