Machine learning prediction algorithm flow chart.

<div><p>Antimicrobial peptides (AMPs) are excellent at fighting many different infections. This demonstrates how important it is to make new AMPs that are even better at eliminating infections. The fundamental transformation in a variety of scientific disciplines, which led to the emerge...

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Bibliographic Details
Main Author:	Ahmad M. Al-Omari (20460931) (author)
Other Authors:	Yazan H. Akkam (20460934) (author), Ala’a Zyout (17636912) (author), Shayma’a Younis (20460937) (author), Shefa M. Tawalbeh (9445724) (author), Khaled Al-Sawalmeh (20460940) (author), Amjed Al Fahoum (17636909) (author), Jonathan Arnold (25901) (author)
Published:	2024
Subjects:	Biochemistry Biotechnology Immunology Infectious Diseases Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified two distinct methodologies investigation assesses 1 computed physicochemical attributes 9 %, respectively 360 peptide sequences 34 physicochemical characteristics fundamental peptide features learning classification approach presented significant opportunities fundamental input data leveraging deep learning make new amps generating potent peptides div >< p escherichia coli </ machine learning techniques deep learning coli </ fundamental transformation machine learning biological data significant time significant implications e </ single microorganism signal images second methods second method scientific disciplines research contributes proposed methods negative bacterium model organism main purpose innovative amp exhibit anti even better eliminating infections could potentially cost reductions based treatments anticancer peptides >), however
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Machine learning prediction algorithm flow chart.

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