Identifying the most appropriate pattern for identification of gene expression changes in ovarian cancer using microarray
المؤلفون المشاركون
Chaichian, Shahla
Moazzami, Bahram
Iskandari, Masumi
Faroughi, Pouya
Karimi, Asrin
Jasmi, Fatimah
DeKoning, Jenefer J.
المصدر
Iranian Red Crescent Medical Journal
العدد
المجلد 21، العدد 7 (31 يوليو/تموز 2019)، ص ص. 1-10، 10ص.
الناشر
تاريخ النشر
2019-07-31
دولة النشر
الإمارات العربية المتحدة
عدد الصفحات
10
التخصصات الرئيسية
الموضوعات
الملخص EN
Background: Microarray technology is an accurate method for recognition of disease association gene alterations.
However, there still is not an effective approach for the evaluation of gene expression in ovarian cancer.
Objectives: A reliable approach is described to identify genes associated with ovarian cancer.
Methods: Microarray gene expression data analysis was applied to correct systematic differences through four different normalization methods; LOESS, 3D LOESS, and neural network (NN3, NN4).
Then, three different clustering methods of K-means, fuzzy C-means, and hierarchical methods were examined on corrected gene expression values.
The proposed approach was tested on a reliable source of genes’ information, where the entropy of genes in samples and Euclidean distance were used for gene selection.
Results: Our findings revealed that a neural-network-based normalizationmethodcould better control the effects of non-biological variations from microarray data.
Moreover, the hierarchical clustering was more effective compared to other methods, and resulted in the identification of three genes, including BC029410, DUSP2, and ILDR1, as candidates for disease-association genes.
Conclusions: According to the finding of the present study, hierarchical clustering with nonlinear-based normalization could have the ability to prioritize genes for ovarian cancer.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Iskandari, Masumi& Chaichian, Shahla& DeKoning, Jenefer J.& Moazzami, Bahram& Faroughi, Pouya& Karimi, Asrin…[et al.]. 2019. Identifying the most appropriate pattern for identification of gene expression changes in ovarian cancer using microarray. Iranian Red Crescent Medical Journal،Vol. 21, no. 7, pp.1-10.
https://search.emarefa.net/detail/BIM-892343
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Iskandari, Masumi…[et al.]. Identifying the most appropriate pattern for identification of gene expression changes in ovarian cancer using microarray. Iranian Red Crescent Medical Journal Vol. 21, no. 7 (Jul. 2019), pp.1-10.
https://search.emarefa.net/detail/BIM-892343
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Iskandari, Masumi& Chaichian, Shahla& DeKoning, Jenefer J.& Moazzami, Bahram& Faroughi, Pouya& Karimi, Asrin…[et al.]. Identifying the most appropriate pattern for identification of gene expression changes in ovarian cancer using microarray. Iranian Red Crescent Medical Journal. 2019. Vol. 21, no. 7, pp.1-10.
https://search.emarefa.net/detail/BIM-892343
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Text in English ; abstracts in .
رقم السجل
BIM-892343
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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