Fitness values for all experiments.

<div><p>DNA splice junction classification is a crucial job in computational biology. The challenge is to predict the junction type (IE, EI, or N) from a given DNA sequence. Predicting junction type is crucial for understanding gene expression patterns, disease causes, splicing regulatio...

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محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Eslam Hamouda (5172083) (author)
مؤلفون آخرون:	Mayada Tarek (5172080) (author)
منشور في:	2024
الموضوعات:	Medicine Genetics Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified universal rule guides grey wolf optimizer vast feature space first layer applies exploration ability allows statlog dna dataset given dna sequence reliable feature selection div >< p proposed method divides predicting junction type classification model trained feature selection second layer method using junction type generalization ability ensemble model proposed approach various partitions using cross thus leading thorough examination test sets study presents splicing regulation selected features rna splicing retrieved features remaining held proposed gwo implementation code hybrid approach gene structure finding suggests ensemble learning efficiently search disease causes computational biology comprehensively evaluating classifier ’ 96 %.
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!

Fitness values for all experiments.

مواد مشابهة