A Modular Learning Environment for Protein Modeling

Proceedings of the First International Conference on Intelligent Systems for Molecular Biology, 1993

Volume

Proceedings of the First International Conference on Intelligent Systems for Molecular Biology, 1993

Contents

We propose in this paper a modular learning environment for protein modeling. In this system, the protein modeling problem is tackled in two successive phases. First, partial structural informations are determined via numerical learning techniques. Then, in the second phase, the multiple available informations are combined in paaem matching searches via dynamic programming. It is shown on real problems that various protein structure predictions can be improved in this way, such as secondary structure prediction, alignment of weakly homologous protein sequences or protein model evaluations.