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However, reconstruction of signaling pathways remains a challenge mainly because of the need for systematic approaches for predicting causal relationships, like edge direction and activation\/inhibition among interacting proteins in the signal flow. We propose an approach for predicting signaling pathways that integrates protein interactions, gene expression, phenotypes, and protein complex information. Our method first finds candidate pathways using a directed-edge-based algorithm and then defines a graph model to include causal activation relationships among proteins, in candidate pathways using cell cycle gene expression and phenotypes to infer consistent pathways in yeast. Then, we incorporate protein complex coverage information for deciding on the final predicted signaling pathways. We show that our approach improves the predictive results of the state of the art using different ranking metrics.<\/jats:p>","DOI":"10.1142\/s0219720019500112","type":"journal-article","created":{"date-parts":[[2019,6,24]],"date-time":"2019-06-24T07:34:24Z","timestamp":1561361664000},"page":"1950011","source":"Crossref","is-referenced-by-count":0,"title":["Cell cycle and protein complex dynamics in discovering signaling pathways"],"prefix":"10.1142","volume":"17","author":[{"given":"Daniel","family":"Inostroza","sequence":"first","affiliation":[{"name":"Computer Science Department, University of Concepci\u00f3n, Edmundo Larenas, Concepci\u00f3n 4030000, Chile"}]},{"given":"Cecilia","family":"Hern\u00e1ndez","sequence":"additional","affiliation":[{"name":"Computer Science Department, University of Concepci\u00f3n, Edmundo Larenas, Concepci\u00f3n 4030000, Chile"},{"name":"Center for Biotechnology and Bioengineering (CeBiB), Santiago, 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