PlanNET: homology-based predicted interactome for multiple planarian transcriptomes

Motivation: Planarians are emerging as a model organism to study regeneration in animals. However, the little available data of protein-protein interactions hinders the advances in understanding the mechanisms underlying its regenerating capabilities. Results: We have developed a protocol to predict...

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Detalles Bibliográficos
Autores: Castillo-Lara, Sergio, Abril Ferrando, Josep Francesc, 1970-
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2017
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/195344
Acceso en línea:https://hdl.handle.net/2445/195344
Access Level:acceso abierto
Palabra clave:Planària (Gènere)
RNA
Planaria (Genus)
Descripción
Sumario:Motivation: Planarians are emerging as a model organism to study regeneration in animals. However, the little available data of protein-protein interactions hinders the advances in understanding the mechanisms underlying its regenerating capabilities. Results: We have developed a protocol to predict protein-protein interactions using sequence homology data and a reference Human interactome. This methodology was applied on eleven Schmidtea mediterranea transcriptomic sequence datasets. Then, using Neo4j as our database manager, we developed PlanNET, a web application to explore the multiplicity of networks and the associated sequence annotations. By mapping RNA-seq expression experiments onto the predicted networks, and allowing a transcript-centric exploration of the planarian interactome, we provide researchers with a useful tool to analyse possible pathways and to design new experiments, as well as a reproducible methodology to predict, store, and explore protein interaction networks for non-model organisms. Availability: The web application PlanNET is available at https://compgen.bio.ub.edu/PlanNET. The source code used is available at https://compgen.bio.ub.edu/PlanNET/downloads.