Computer programs for the characterization of protein coding genes

On research subsystems and their integration in the computer-supported part of hospital information systems

Taking as an example the special research programme ('Sonderforschungsbereich') in leukemia research and immunogenetics (SFB120) of the University of Tübingen, we intend to discuss how research subsystems should be built up, which functions they should take over and which network architecture is suitable. Furthermore, we examined to what extent research subsystems can be integrated in the computer-supported part of hospital information systems. It can easily be seen that no general solution exists for the structuring. The structure depends rather upon the specific problems and information requirements of individual research units. The clinical environment must be taken into account if research subsystems are to be integrated into the computer-supported part of a hospital information system. Especially in regard to the data protection aspect, we must keep in mind that the connection between subsystems must not necessarily result in the setup of a network for the corresponding computer systems.

Probability of coding of a DNA sequence: an algorithm to predict translated reading frames from their thermodynamic characteristics

An algorithm to determine the probability that a reading frame codifies for a protein is presented. It is based on the results of our previous studies on the thermodynamic characteristics of a translated reading frame. We also develop a prediction procedure to distinguish between coding and non-coding reading frames. The procedure is based on the characteristics of the putative product of the DNA sequence and not on periodicity characteristics of the sequence, so the prediction is not biased by the presence of overlapping translated reading frames or by the presence of translated reading frames on the complementary DNA strand.

Statistical evaluation of the coding capacity of complementary DNA strands

Two independent methods are used to evaluate the protein-coding information content in different classes of DNA sequences. The first method allows to evaluate the statistical relevance of finding unidentified reading frames, longer than 100 codons, on both DNA strands of: a) 117 DNA sequences that code for 142 nuclear proteins; b) 39 stable RNA coding sequences and c) 36 other DNA sequences which include regulatory and as yet unknown function sequences. The finding of 50 reading frames longer than 100 codons (complementary inverted proteins or c.i.p. genes) located on the DNA strand complementary to the protein-coding one is drastically in excess of the number predicted by chance alone. An independent method (testcode) applied to c.i.p. gene sequences, which assigns the probability of coding to a given sequence, predicts that more than 50% of these genes are translated in a functional product. These analyses indicate the existence of a new class of protein-coding genes, located on the DNA sequences complementary to the protein-coding DNA strand.