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Clustering Expert-Based Gene Expression Profiling in Lung Cancer

المصدر: المجلة العلمية للاقتصاد والتجارة
الناشر: جامعة عين شمس - كلية التجارة
المؤلف الرئيسي: Farouq, Muhamed Wael (Author)
المجلد/العدد: ع3
محكمة: نعم
الدولة: مصر
التاريخ الميلادي: 2018
الشهر: أكتوبر
الصفحات: 391 - 402
ISSN: 2636-2562
رقم MD: 1066406
نوع المحتوى: بحوث ومقالات
اللغة: الإنجليزية
قواعد المعلومات: EcoLink
مواضيع:
كلمات المؤلف المفتاحية:
Clustering | Fusion | Dempster Shafer | Evidence Theory | Microarray | Unsupervised Learning | Association Rules | Data mining | Fuzzy Clustering | Short Exposure | Long Exposure
رابط المحتوى:
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المستخلص: The microarray has made the analysis of the dynamics and interactions of thousands of genes simultaneously possible. The inference of expression data is guided by the following facts: expression data are highly dimensional and complex. Another fact is that dynamic relations exist among thousands of genes simultaneously and/or sequentially. Dynamic relations on one hand may reveal cascade interactions between genes that is the expression of one gene may alter the transcription rate of another one. On the other hand, dynamic relations may show coherent patterns that is genes with similar expressions suggest that they are more likely co-regulating each other or to be regulated by a parental gene. Expression data might also show both cascade interactions and coherent patterns. Further complicating the inference is the fact that sample profile-to-gene profile ratio is usually very small. The fusion NT clusters and their boundaries act as a prespecified clustering structure for the SE post 4 hrs, LE post 1 hr, LE post 2 hrs and LE post 4 hrs. Then each expert is searching for the optimal clustering solution for a clustering structure of 4 clusters. The combinatorial clustering solution for the three LE post 1 hr experts is presented. In the same manner, the fusion of the three LE post 2 hrs and the three LE post 4 hrs experts are illustrated. The fusion results reveal a very close clusters gene size.

ISSN: 2636-2562

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