Prediction of relative binding motifs of biologically active...

Details Prediction of relative binding motifs of biologically active... Prediction of relative binding motifs of biologically active...

G - Physics

06

F

G06F 15/18 (2006.01) C07K 1/00 (2006.01)

Patent

CA 2290977

A general neural network based method and system for identifying peptide binding motifs from limited experimental data. In particular, an artificial neural network (1) is trained with peptide with known sequence and function (i.e., bindings strength) identified from a phase display library. The artificial neural network (1) is then challenged with unknown peptide, and predicts relative binding motifs. Analysis of the unknown peptide validate the predictive capability of the artificial neural network (1).

La présente invention concerne un système et un procédé à réseau neuronal pour identifier des motifs de liaison de peptides à partir de données expérimentales limitées. On éduque, en particulier, un réseau neuronal artificiel (1) en utilisant des peptides à séquence connue, puis on identifie une fonction (c'est-à-dire, une force de liaison) à partir d'une bibliothèque d'affiche de phase. On compare ensuite le réseau neuronal artificiel (1) à des peptides inconnus, puis on prédit des motifs de liaison relatifs. L'analyse des peptides inconnus valide la capacité prédictive du réseau neuronal artificiel (1).

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