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The core of a 6502 machine language program for DNA sequence analysis on Apple II microcomputer is described. Use of a binary coding of nucleotides allows interactive data manipulation on a low-cost configuration with execution times similar to those of larger computers. The PEGASE system should prove useful and easy to use in routine sequence handling and experiment design.

DNAid is a full screen and multi-window sequence editor designed as an aid for the easy manipulation of DNA and protein sequences on Macintosh computers. In addition to the classical editing capabilities, powerful analysis and search functions are available from within the editor. Restriction mapping, translation and alignment of homologous sequences are supported by DNAid, furthermore a pattern matching language is included which allows searches for user-defined strict or fuzzy signals within biological sequences. Patterns are translated into finite state automata which allow very efficient searches.

During the course of determining the sequence of a large DNA fragment, it is necessary to cross-check numerous gel readings from different DNA fragments, in order to track and eliminate mistakes. An algorithm is presented that takes advantage of the high degree of homology between such sequences to construct an alignment of the matching regions. It does not require knowledge of a starting homology zone, neither large memory areas, even for sequences of several kilobases, and it can overcome large gaps or mismatch zones that correspond for instance to misinterpretation of compressions on sequence gels. This algorithm has been implemented in 6502 assembly language on an Apple II computer as an extension to the PEGASE sequence handling system.

A program is described for estimating enzymatic parameters from experimental data using Apple Macintosh computers. MC-Fit uses iterative least-square fitting and Monte-Carlo sampling to get accurate estimates of the confidence limits. This approach is more robust than the conventional covariance matrix estimation, especially in cases where experimental data is partially lacking or when the standard error on individual measurements is large. This happens quite often when analysing the properties of variant enzymes obtained by mutagenesis, as these can have severely impaired activities and reduced affinities for their substrates.