Transcription factor-binding site identification and gene classification via fusion of the supervised-weighted discrete kernel clustering and support vector machine

Insuk Sohn; Jooyong Shim; Changha Hwang; Sujong Kim; Jae Won Lee

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Transcription factor-binding site identification and gene classification via fusion of the supervised-weighted discrete kernel clustering and support vector machine

机译：通过监督加权离散核聚类和支持向量机的融合实现转录因子结合位点的鉴定和基因分类

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摘要

The genetic regulatory mechanism heavily influences a substantial portion of biological functions and processes needed to sustain life. For a comprehensive mechanistic understanding of biological processes, it is important to identify the common transcription factor (TF) binding sites (TFBSs) from a set of promoter sequences of co-regulated genes and classify genes that are co-regulated by certain TFs, therefore to provide an insight into the mechanism that underlies the interaction among the co-regulated genes and complicate genetic regulation. We propose a new supervised-weighted discrete kernel clustering (SWDKC) classification method for the identification of TFBS and the classification of gene. Our SWDKC method gave smaller misclassification error rate than the other methods on both the simulated data and the real NF-κB data. We verify that the selected over-represented TFBSs serve informative TFBSs from a biological point of view.

机译：基因调节机制严重影响了维持生命所需的大部分生物学功能和过程。为了全面了解生物学过程，重要的是从一组共同调控基因的启动子序列中鉴定出公共转录因子（TF）结合位点（TFBS），并对由某些TF共同调控的基因进行分类，因此提供对共同调控基因之间相互作用基础的机制的见解，并使基因调控复杂化。我们提出了一种新的监督加权离散核聚类（SWDKC）分类方法，用于TFBS的鉴定和基因分类。在模拟数据和实际NF-κB数据上，我们的SWDKC方法给出的误分类错误率均比其他方法小。我们从生物学的角度验证所选的超额代表的TFBS提供了有益的TFBS。

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来源
《Journal of applied statistics》 |2014年第4期|573-581|共9页
作者
Insuk Sohn; Jooyong Shim; Changha Hwang; Sujong Kim; Jae Won Lee;
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作者单位

Samsung Cancer Research Institute, Samsung Medical Center, Seoul 137-710, Korea;

Department of Data Science, Institute of Statistical Information, Inje University, Kyungnam 621-749, Korea;

Department of Applied Statistics, Dankook University, Gyeonggido 448-160, Korea;

R&D Center, Komipharm International Co., LTD, Kyounggi-do 429-450, Korea;

Department of Statistics, Korea University, Seoul 136-701, Korea;

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正文语种 eng
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关键词
supervised clustering; transcription factor-binding site; transcription factor; gene classification; support vector machines;

机译：有监督的聚类;转录因子结合位点;转录因子基因分类支持向量机;

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Transcription factor-binding site identification and gene classification via fusion of the supervised-weighted discrete kernel clustering and support vector machine

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