腺瘤微阵列基因表达数据二值包含-最大双聚类算法的实现

Syamira Merina, A. Bustamam, Gianinna Ardaneswari
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引用次数: 0

摘要

腺瘤是一种良性肿瘤,位于组织表皮层。腺瘤可以转变为恶性肿瘤,也就是腺癌。目前正在发展的一种分子生物学数据形式,即微阵列基因表达数据。微阵列技术可用于肿瘤领域的检测和研究。处理和分析微阵列基因数据的一种方法是双聚类。在本研究中,作者将使用一种双聚类方法,即二值包含最大算法,并将其实现在微阵列基因表达数据上。该算法将在包含7070个基因的结肠腺瘤数据上执行,其中包含4个腺瘤细胞样本和4个正常细胞样本。这个过程只用了不到一秒的时间,就得到了由25个基因组成的22个双聚类。
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Implementation of The Binary Inclusion-Maximal Biclustering Algorithm on Adenoma Microarray Gene Expression Data
Adenoma is a benign type of tumor in the epidermal layer of tissue. Adenoma can turn into malignant cancer which is then called Adenocarcinoma. There is a form of molecular biology data which is developing today, namely microarray gene expression data. Microarray can be used for detection and research in the field of oncology. One method for processing and analyzing microarray gene data is by biclustering. In this study, the writer will be using one method of biclustering, the Binary Inclusion-Maximal algorithm, and implement it on microarray gene expression data. The algorithm will be performed on Colon Adenoma data consisting of 7070 genes with four adenoma cell samples and four normal cell samples. The implementation took less than one second and resulted in 22 biclusters composed of 25 genes.
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