Computer, Electrical and Mathematical Sciences and Engineering Division, Computational Bioscience Research Centre, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.
Bioinformatics. 2018 Sep 1;34(17):i857-i865. doi: 10.1093/bioinformatics/bty605.
Function annotations of gene products, and phenotype annotations of genotypes, provide valuable information about molecular mechanisms that can be utilized by computational methods to identify functional and phenotypic relatedness, improve our understanding of disease and pathobiology, and lead to discovery of drug targets. Identifying functions and phenotypes commonly requires experiments which are time-consuming and expensive to carry out; creating the annotations additionally requires a curator to make an assertion based on reported evidence. Support to validate the mutual consistency of functional and phenotype annotations as well as a computational method to predict phenotypes from function annotations, would greatly improve the utility of function annotations.
We developed a novel ontology-based method to validate the mutual consistency of function and phenotype annotations. We apply our method to mouse and human annotations, and identify several inconsistencies that can be resolved to improve overall annotation quality. We also apply our method to the rule-based prediction of regulatory phenotypes from functions and demonstrate that we can predict these phenotypes with Fmax of up to 0.647.
基因产物的功能注释和基因型的表型注释提供了有价值的分子机制信息，这些信息可以被计算方法利用来识别功能和表型的相关性，增进我们对疾病和病理生物学的理解，并发现药物靶点。确定功能和表型通常需要进行耗时且昂贵的实验；此外，创建注释还需要管理员根据报告的证据做出断言。支持验证功能和表型注释的相互一致性以及从功能注释预测表型的计算方法，将极大地提高功能注释的实用性。
我们开发了一种基于本体的新方法来验证功能和表型注释的相互一致性。我们将我们的方法应用于小鼠和人类的注释，并确定了一些可以解决的不一致性，以提高整体注释质量。我们还将我们的方法应用于基于规则的从功能预测调节表型，并证明我们可以用高达 0.647 的 Fmax 预测这些表型。
Zotero 插件