文章基本信息

标题：An integrated network of Arabidopsis growth regulators and its use for gene prioritization
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作者：Ehsan Sabaghian ; Zuzanna Drebert ; Dirk Inzé 等
期刊名称：Scientific Reports
电子版ISSN：2045-2322
出版年度：2015
卷号：5
期号：1
DOI：10.1038/srep17617
语种：English
出版社：Springer Nature
摘要：Elucidating the molecular mechanisms that govern plant growth has been an important topic in plant research, and current advances in large-scale data generation call for computational tools that efficiently combine these different data sources to generate novel hypotheses. In this work, we present a novel, integrated network that combines multiple large-scale data sources to characterize growth regulatory genes in Arabidopsis, one of the main plant model organisms. The contributions of this work are twofold: first, we characterized a set of carefully selected growth regulators with respect to their connectivity patterns in the integrated network, and, subsequently, we explored to which extent these connectivity patterns can be used to suggest new growth regulators. Using a large-scale comparative study, we designed new supervised machine learning methods to prioritize growth regulators. Our results show that these methods significantly improve current state-of-the-art prioritization techniques, and are able to suggest meaningful new growth regulators. In addition, the integrated network is made available to the scientific community, providing a rich data source that will be useful for many biological processes, not necessarily restricted to plant growth.