![](/images/graphics-bg.png)
Integrative Deep Learning for Identifying Differentially Expressed (DE) Biomarkers
المؤلفون المشاركون
Lim, Jayeon
Bang, SoYoun
Kim, Jiyeon
Park, Cheolyong
Cho, JunSang
Kim, SungHwan
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-10، 10ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-11-02
دولة النشر
مصر
عدد الصفحات
10
التخصصات الرئيسية
الملخص EN
As a large amount of genetic data are accumulated, an effective analytical method and a significant interpretation are required.
Recently, various methods of machine learning have emerged to process genetic data.
In addition, machine learning analysis tools using statistical models have been proposed.
In this study, we propose adding an integrated layer to the deep learning structure, which would enable the effective analysis of genetic data and the discovery of significant biomarkers of diseases.
We conducted a simulation study in order to compare the proposed method with metalogistic regression and meta-SVM methods.
The objective function with lasso penalty is used for parameter estimation, and the Youden J index is used for model comparison.
The simulation results indicate that the proposed method is more robust for the variance of the data than metalogistic regression and meta-SVM methods.
We also conducted real data (breast cancer data (TCGA)) analysis.
Based on the results of gene set enrichment analysis, we obtained that TCGA multiple omics data involve significantly enriched pathways which contain information related to breast cancer.
Therefore, it is expected that the proposed method will be helpful to discover biomarkers.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Lim, Jayeon& Bang, SoYoun& Kim, Jiyeon& Park, Cheolyong& Cho, JunSang& Kim, SungHwan. 2019. Integrative Deep Learning for Identifying Differentially Expressed (DE) Biomarkers. Computational and Mathematical Methods in Medicine،Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1130745
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Lim, Jayeon…[et al.]. Integrative Deep Learning for Identifying Differentially Expressed (DE) Biomarkers. Computational and Mathematical Methods in Medicine No. 2019 (2019), pp.1-10.
https://search.emarefa.net/detail/BIM-1130745
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Lim, Jayeon& Bang, SoYoun& Kim, Jiyeon& Park, Cheolyong& Cho, JunSang& Kim, SungHwan. Integrative Deep Learning for Identifying Differentially Expressed (DE) Biomarkers. Computational and Mathematical Methods in Medicine. 2019. Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1130745
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1130745
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
![](/images/ebook-kashef.png)
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر
![](/images/kashef-image.png)