Gene Expression Profiling of Colorectal Tumors and Normal Mucosa by Microarrays Meta-Analysis Using Prediction Analysis of Microarray, Artificial Neural Network, Classification, and Regression Trees
المؤلفون المشاركون
Lee, Chia-Cheng
Chang, Chi-Wen
Liu, Yao-Chi
Huang, Chi-Shuan
Su, Sui-Lun
Chou, Hsiu-Ling
Lin, Fu-Gong
Chang, Yu-Tien
Yao, Chung-Tay
Chu, Chi-Ming
Chen, Kang-Hua
Chou, Yu-Ching
Wetter, Thomas
Terng, Harn-Jing
المصدر
العدد
المجلد 2014، العدد 2014 (31 ديسمبر/كانون الأول 2014)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2014-05-19
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
Background.
Microarray technology shows great potential but previous studies were limited by small number of samples in the colorectal cancer (CRC) research.
The aims of this study are to investigate gene expression profile of CRCs by pooling cDNA microarrays using PAM, ANN, and decision trees (CART and C5.0).
Methods.
Pooled 16 datasets contained 88 normal mucosal tissues and 1186 CRCs.
PAM was performed to identify significant expressed genes in CRCs and models of PAM, ANN, CART, and C5.0 were constructed for screening candidate genes via ranking gene order of significances.
Results.
The first screening identified 55 genes.
The test accuracy of each model was over 0.97 averagely.
Less than eight genes achieve excellent classification accuracy.
Combining the results of four models, we found the top eight differential genes in CRCs; suppressor genes, CA7, SPIB, GUCA2B, AQP8, IL6R and CWH43; oncogenes, SPP1 and TCN1.
Genes of higher significances showed lower variation in rank ordering by different methods.
Conclusion.
We adopted a two-tier genetic screen, which not only reduced the number of candidate genes but also yielded good accuracy (nearly 100%).
This method can be applied to future studies.
Among the top eight genes, CA7, TCN1, and CWH43 have not been reported to be related to CRC.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Chu, Chi-Ming& Yao, Chung-Tay& Chang, Yu-Tien& Chou, Hsiu-Ling& Chou, Yu-Ching& Chen, Kang-Hua…[et al.]. 2014. Gene Expression Profiling of Colorectal Tumors and Normal Mucosa by Microarrays Meta-Analysis Using Prediction Analysis of Microarray, Artificial Neural Network, Classification, and Regression Trees. Disease Markers،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-486822
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Chu, Chi-Ming…[et al.]. Gene Expression Profiling of Colorectal Tumors and Normal Mucosa by Microarrays Meta-Analysis Using Prediction Analysis of Microarray, Artificial Neural Network, Classification, and Regression Trees. Disease Markers No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-486822
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Chu, Chi-Ming& Yao, Chung-Tay& Chang, Yu-Tien& Chou, Hsiu-Ling& Chou, Yu-Ching& Chen, Kang-Hua…[et al.]. Gene Expression Profiling of Colorectal Tumors and Normal Mucosa by Microarrays Meta-Analysis Using Prediction Analysis of Microarray, Artificial Neural Network, Classification, and Regression Trees. Disease Markers. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-486822
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-486822
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