title: Predicting link directionality in gene regulation from gene expression profiles using volatility-constrained correlation.
abstract: To uncover potential disease molecular pathways and signaling networks, we do not only need undirected maps but also we need to infer the directionality of functional or physical interactions between cellular components. A wide range of methods for identifying functional interactions between genes relies on correlations between experimental gene expression measurements to some extent. However, the standard Pearson or Spearman correlation-based approaches can only determine undirected correlations between cellular components. Here, we apply a volatility-constrained correlation method for gene expression profiles that offers a new metric to capture directionality of interactions between genes. To evaluate the predictions we used four datasets distributed by the DREAM5 network inference challenge including an in silico-constructed network and three organisms such as S. aureus, E. coli and S. cerevisiae. The predictions performed by our proposed method were compared to a gold standard of experimentally verified directionality of genetic regulatory links. Our findings show that our method successfully predicts the genetic interaction directionality with a success rate higher than 0.5 with high statistical significance.
authors.affiliation: Faculty of Social Information Studies, Otsuma Women's University, 2-7-1 Karakida, Tama-shi, Tokyo 206-8540, Japan. Electronic address: ochiai@otsuma.ac.jp.
authors.forename: Tomoshiro
authors.initials: T
authors.lastname: Ochiai
authors.affiliation: Department of Information Science, Faculty of Science, Toho University, Miyama 2-2-1, Funabashi, Chiba 274-8510, Japan. Electronic address: nacher@is.sci.toho-u.ac.jp.
authors.forename: Jose C
authors.initials: JC
authors.lastname: Nacher
mesh_terms: D004926:Escherichia coli / Q000235:genetics; D005544:Forecasting; D020869:Gene Expression Profiling / Q000379:methods*; D053263:Gene Regulatory Networks / Q000502:physiology*; D012441:Saccharomyces cerevisiae / Q000235:genetics; D013211:Staphylococcus aureus / Q000235:genetics; D014835:Volatilization
keywords: Gene expression data analysis; Gene expression profile; Regulatory interaction inference; Statistical modeling