RT Generic
T1 Modular multi-relational framework for gene group function prediction
A1 García Jiménez, Beatriz
A1 Ledezma Espino, Agapito Ismael
A1 Sanchis de Miguel, María Araceli
AB Determining the functions of genes is essential for understanding how the metabolisms work, and for trying to solve their malfunctions. Genes usually work in groups rather than isolated, so functions should be assigned to gene groups and not to individual genes. Moreover, the genetic knowledge has many relations and is very frequently changeable. Thus, a propositional ad-hoc approach is not appropriate to deal with the gene group function prediction domain. We propose the Modular Multi-Relational Framework (MMRF), which faces the problem from a relational and flexible point of view. The MMRF consists of several modules covering all involved domain tasks (grouping, representing and learning using computational prediction techniques). A specific application is described, including a relational representation language, where each module of MMRF is individually instantiated and refined for obtaining a prediction under specific given conditions.
YR 2009
FD 2009
LK https://hdl.handle.net/10016/9784
UL https://hdl.handle.net/10016/9784
LA eng
NO Poster of: 19th International Conference on Inductive Logic Programming (ILP 2009), Leuven, Belgium, 2 - 4 Jul, 2009
NO The research reported here has been supported byCICYT, TRA2007-67374-C02-02 project.
DS e-Archivo
RD 20 may. 2024