Smart approach for the design of highly selective aptamer-based biosensors

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SUMMARY

    No machine_learning models for small aptamer molecules have been reported and they can have a significant impact on several applications such as DNA, toxin, heavy metal, antibiotic, ion, molecular marker, and virus detection. Isolating aptamers for a specific target by employing bioinformatics, machine_learning, and a rational design represents a challenge with huge potential. The authors developed, by means of bioinformatics tools and machine_learning, a deep learning model able to learn the complex features of an aptamer-target system starting from training data obtained from previously isolated sequences (through standard SELEX). For the target`s . . .

     

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