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首页> 外文会议>2016 International Conference on Microelectronics, Computing and Communications >Disease associated protein complex detection: A multi-objective evolutionary approach
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Disease associated protein complex detection: A multi-objective evolutionary approach

机译：疾病相关蛋白复合物检测：多目标进化方法

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Biological networks such as protein-protein interaction networks (PPINs) play a crucial role in cell biology of an organism and are widely studied in bioinformatics and biostatistics. Scores of high throughput techniques are used to identify PPIs which are then used to compile PPINs of an organism. Detection of protein complexes that are associated with diseases is another ongoing challenge. Consequently, methods have been developed that use PPINs in order to predict or identify disease associated protein complexes. Here we have modeled this task as a multi-objective optimization problem and developed a multi-objective evolutionary framework called MODAPROC to detect protein complexes associated with human diseases. MODAPROC considered three objective functions viz., density, number of outward interactions, and disease associations of a protein complex. Density and disease associations are to be maximized while outward interactions are minimized here. We have analyzed the resulting protein complexes and their association with different disorders. Moreover, we have detected some key properties of the disease associated protein complexes as well as classified them according to different disorders. MODAPROC is fast, robust, and provides a good analysis tool for finding and discovering obscure disease specific gene clusters and can be extended using other domain specific objective functions.
机译：诸如蛋白质-蛋白质相互作用网络（PPIN）之类的生物网络在生物体的细胞生物学中起着至关重要的作用，并且在生物信息学和生物统计学中得到了广泛的研究。数十种高通量技术可用于识别PPI，然后将其用于编译生物体的PPIN。与疾病相关的蛋白质复合物的检测是另一个持续的挑战。因此，已经开发出使用PPIN以预测或鉴定疾病相关蛋白复合物的方法。在这里，我们将此任务建模为一个多目标优化问题，并开发了一个称为MODAPROC的多目标进化框架，以检测与人类疾病相关的蛋白质复合物。 MODAPROC考虑了三个目标函数，即蛋白质复合物的密度，向外相互作用的数量和疾病关联。密度和疾病的关联要最大化，而向外的相互作用则要最小化。我们已经分析了所得的蛋白质复合物及其与不同疾病的关系。此外，我们已经检测到了疾病相关蛋白复合物的一些关键特性，并根据不同的疾病对其进行了分类。 MODAPROC快速，强大，并且为发现和发现晦涩的疾病特定基因簇提供了一个很好的分析工具，可以使用其他领域特定的目标功能进行扩展。

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