Kaimal Vivek, Sardana Divya, Bardes Eric E, Gudivada Ranga Chandra, Chen Jing, Jegga Anil G
Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Methods Mol Biol. 2011;700:241-59. doi: 10.1007/978-1-61737-954-3_16.
Although a number of computational approaches have been developed to integrate data from multiple sources for the purpose of predicting or prioritizing candidate disease genes, relatively few of them focus on identifying or ranking drug targets. To address this deficit, we have developed an approach to specifically identify and prioritize disease and drug candidate genes. In this chapter, we demonstrate the applicability of integrative systems-biology-based approaches to identify potential drug targets and candidate genes by employing information extracted from public databases. We illustrate the method in detail using examples of two neurodegenerative diseases (Alzheimer's and Parkinson's) and one neuropsychiatric disease (Schizophrenia).
尽管已经开发了许多计算方法来整合来自多个来源的数据，以预测候选疾病基因或对其进行优先级排序，但其中相对较少的方法专注于识别药物靶点或对其进行排名。为了弥补这一不足，我们开发了一种专门识别疾病和药物候选基因并对其进行优先级排序的方法。在本章中，我们通过利用从公共数据库中提取的信息，展示了基于整合系统生物学的方法在识别潜在药物靶点和候选基因方面的适用性。我们使用两种神经退行性疾病（阿尔茨海默病和帕金森病）和一种神经精神疾病（精神分裂症）的例子详细说明了该方法。
