دورية أكاديمية

Immunoglobulin Classification Based on FC* and GC* Features

التفاصيل البيبلوغرافية
العنوان: Immunoglobulin Classification Based on FC* and GC* Features
المؤلفون: Hao Wan, Jina Zhang, Yijie Ding, Hetian Wang, Geng Tian
المصدر: Frontiers in Genetics, Vol 12 (2022)
بيانات النشر: Frontiers Media S.A., 2022.
سنة النشر: 2022
المجموعة: LCC:Genetics
مصطلحات موضوعية: immunoglobulin classification, machine learning, key feature extraction, MRMD, autoprop, Genetics, QH426-470
الوصف: Immunoglobulins have a pivotal role in disease regulation. Therefore, it is vital to accurately identify immunoglobulins to develop new drugs and research related diseases. Compared with utilizing high-dimension features to identify immunoglobulins, this research aimed to examine a method to classify immunoglobulins and non-immunoglobulins using two features, FC* and GC*. Classification of 228 samples (109 immunoglobulin samples and 119 non-immunoglobulin samples) revealed that the overall accuracy was 80.7% in 10-fold cross-validation using the J48 classifier implemented in Weka software. The FC* feature identified in this study was found in the immunoglobulin subtype domain, which demonstrated that this extracted feature could represent functional and structural properties of immunoglobulins for forecasting.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1664-8021
Relation: https://www.frontiersin.org/articles/10.3389/fgene.2021.827161/full; https://doaj.org/toc/1664-8021
DOI: 10.3389/fgene.2021.827161
URL الوصول: https://doaj.org/article/48f98b0c12a249ff9e879de5ad1aa5b9
رقم الأكسشن: edsdoj.48f98b0c12a249ff9e879de5ad1aa5b9
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:16648021
DOI:10.3389/fgene.2021.827161