Biomedical subjects

J Sallantin

Publications and source records attributed to J Sallantin.

6 recordsLinked to original sources

PubMed1990

PCDRA: PC interactive molecular representation and modeling system.

PCDRA was designed to provide the average biologist with a user-friendly molecular display on a low-cost personal computer. The package is menu driven and is built so that a biologist, with little or no computing knowledge, finds it easy to use. The system gives a color representation with depth cueing of a protein whose atomic coordinates are stored as a PDB file. Moreover, the system presents several features similar to HYDRA and therefore is a good introduction to molecular graphics, especially for beginners in protein modeling.

Computer Graphics↗

PubMed1985

Localization of the initiation of translation in messenger RNAs of prokaryotes by learning techniques.

Learning processes are applied to the recognition of protein coding regions in prokaryotes. Non-contradictory, statistical and logical rules are deduced from a set of known examples of coding sequences. These rules enable to build characteristic patterns on the m-RNA upstream of the initiating codon. These rules are applied with success to recognize more than 180 coding sequences and to detect and/or eliminate hypothetical reading frames or unknown genes.

Bacteria↗

PubMed1985

Search for promoter sites of prokaryotic DNA using learning techniques.

Using learning techniques previously described in this journal, we have built an expert system able to point to the start DNA point of a sequence and therefore to recognize a promoter. However, to build this system, we have focused on the TATA box and its environment. We have used this expert system to look for new promoters and also to construct new promoters. The results obtained are discussed.

Base Sequence↗

PubMed1985

Computer search of calcium binding sites in a gene data bank: use of learning techniques to build an expert system.

Using a learning set of 28 sequences able to bind calcium (each sequence is 12 residues long), we have built two filters by learning on this set. The first filter uses a pattern-matching technique and the second one takes into account the environment of amino-acids. These two filters have been used to find new calcium-binding proteins in a data bank. The results are discussed.

Amino Acid Sequence↗

PubMed1985

[Localization of initiating codons in RNA prokaryotes messengers by learning technics].

Learning processes are applied to the recognition of protein coding regions in prokaryotes. Non-contradictory, statistical rules are deduced from a set of known examples of coding regions. These rules allow us to build characteristic patterns on the m-RNA upstream the initiating codon. These rules are applied to recognize more than 180 coding sequences.

Cell Physiological Phenomena↗

PubMed1981

[The use of pattern recognition for analysing the possible relation between molecular structure of polycyclic hydrocarbons and their carcinogenicity].

Pattern recognition has been used for investigating the part played by the molecular structure of polycyclic hydrocarbons in their carcinogenic action. A series of molecules has been considered, whose physicochemical properties are known to be closely related to the number and location of their aromatic rings. From a pattern recognition program and two learning subsets (carcinogenic and non carcinogenic molecules), it has been shown that (i) the shape of the molecule is correlated with its carcinogenic power; (ii) an index of carcinogenicity can be estimated for any molecule in the considered set.

Carcinogens↗