Biomedical subjects
Publications and source records attributed to M F Macchiato.
A statistical method for characterizing nucleotidic sequences based on maximum entropy techniques is presented. The method uses only codon usage tables and takes into account the length of sequences, and preserves the information contained in each codon by a punctual index. We present the methodological aspects of the analysis, showing an application relative to nucleotidic sequences of eukaryotes.
VARIANT, a FORTRAN 77 computer system for storing and retrieving the amino acid replacements in human haemoglobin variants on a multicriterion basis, is presented. The system is transportable and user-friendly, can easily be expanded and can also be used to create a database of the amino acid replacements in families of homologous proteins, becoming an efficient tool for evolutionary studies.
A real-time, machine-independent software for the analysis and manipulation of sequence data is described. The implemented system allows users to read in sequence data from existing data bases, and to edit, manipulate, analyse and align them. It is easy to use and is suitable for routine investigations and to modify sequences in order to create a user customized data base.
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.
A statistical analysis of the autocorrelation characteristics of active polypeptides has been carried out by means of the correlogram method. It is shown that the amino acid sequences of the analysed proteins, considered as a whole, are autocorrelated and that the correlograms characterize each protein reflecting its three-dimensional structure.
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The Montecarlo method is used to computer simulate a random distribution of molecular lengths generated by inducing T4 DNA fragmentation through the decay of 32P atoms introduced in the molecule. Taking into account the experimental conditions we find that the value of alpha for alkali sucrose gradients is 0.46 +/- 0.02 and does not depend on the running time. Our findings also prove that the computer simulation can be utilized to analyze sedimentation profiles of DNA molecules fragmented in vivo.