Model performance over epochs.

<div><p>Protein glycosylation, a vital post-translational modification, is pivotal in various biological processes and disease pathogenesis. Computational approaches, including protein language models and machine learning algorithms, have emerged as valuable tools for predicting <i>...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Ayesha Khalid (7843483) (author)
مؤلفون آخرون:	Afshan Kaleem (648996) (author), Wajahat Qazi (20489179) (author), Roheena Abdullah (641614) (author), Mehwish Iqtedar (641617) (author), Shagufta Naz (641618) (author)
منشور في:	2024
الموضوعات:	Biochemistry Biotechnology Cancer Biological Sciences not elsewhere classified Information Systems not elsewhere classified various biological processes reducing experimental costs machine learning algorithms facilitating biomarker discovery evaluate various parameters div >< p developing targeted therapies 30 %, recall 30 %, precision higher computational resources evolutionary scale model >- glcnac sites >- glcnac modification diverse data types 2 model outperforms 99 %, esm glcnac site prediction glcnac sites 2 model 31 %, glcnac database translational modification model training computational approaches vital post valuable tools traditional models testing predictions study employed specific prediction specific functions protein glycosylation protein function optimal training improved diagnosis future studies findings underscore esm ). disease pathogenesis disease mechanisms approximately 1100 accurate prediction 74 %.
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Model performance over epochs.

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