Whole-genome annotation by using evidence integration in functional-linkage networks
Whole-genome annotation by using evidence integration in functional-linkage networks
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DOI：
10.1073/pnas.0307326101
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发表时间：
2004-03-02
影响因子：
11.1
通讯作者：
Kasif, S
中科院分区：
文献类型：
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作者：
Karaoz, U;Murali, TM;Kasif, S
高通量生物学的出现促进了我们识别新基因的能力的显着提高。大量新发现的基因具有未知的功能作用，尤其是当它们特定于特定谱系或生物体时。这些基因目前被标记为“假设”，可能支持重要的生物细胞功能，并有可能作为医学，诊断或药物基因组学研究的靶标。科学界的一个重要挑战是将这些新预测的基因与可以通过实验筛选验证的生物学功能相关联。在缺乏已知基因的序列或结构同源性的情况下，我们必须依靠先进的生物技术方法，例如DNA芯片和蛋白质 - 蛋白质相互作用筛选以及计算技术，以将推定功能分配给这些基因。在本文中，我们提出了一种有效的方法，用于结合几个高通量实验筛选中获得的生物学证据，并以提供一致的功能分配的方式整合到假设基因的方式。我们使用传播图的可视化方法来说明支持算法产生的功能分配的功能证据流。我们的结果包含许多预测，并提供了有力的证据，表明功能信息的整合确实是提高功能基因组学准确性和鲁棒性的有希望的方向。
The advent of high-throughput biology has catalyzed a remarkable improvement in our ability to identify new genes. A large fraction of newly discovered genes have an unknown functional role, particularly when they are specific to a particular lineage or organism. These genes, currently labeled "hypothetical," might support important biological cell functions and could potentially serve as targets for medical, diagnostic, or pharmacogenomic studies. An important challenge to the scientific community is to associate these newly predicted genes with a biological function that can be validated by experimental screens. In the absence of sequence or structural homology to known genes, we must rely on advanced biotechnological methods, such as DNA chips and protein-protein interaction screens as well as computational techniques to assign putative functions to these genes. In this article, we propose an effective methodology for combining biological evidence obtained in several high-throughput experimental screens and integrating this evidence in a way that provides consistent functional assignments to hypothetical genes. We use the visualization method of propagation diagrams to illustrate the flow of functional evidence that supports the functional assignments produced by the algorithm. Our results contain a number of predictions and furnish strong evidence that integration of functional information is indeed a promising direction for improving the accuracy and robustness of functional genomics.