Title :
GOrevenge: A Novel Generic Reverse Engineering Method for the Identification of Critical Molecular Players, Through the Use of Ontologies
Author :
Moutselos, Konstantinos ; Maglogiannis, Ilias ; Chatziioannou, Aristotelis
Author_Institution :
Dept. of Comput. Sci. & Biomed. Inf., Univ. of Central Greece, Lamia, Greece
Abstract :
The ever-increasing use of ontologies in modern biological analysis and interpretation facilitates the understanding of the cellular procedures, their hierarchical organization, and their potential interactions at a system´s level. Currently, the gene ontology serves as a paradigm, where through the annotation of whole genomes of certain organisms, genes subsets selected, either from high-throughput experiments or with an established pivotal role regarding the probed disease, can act as a starting point for the exploration of their underlying functional interconnections. This may also aid the elucidation of hidden regulatory mechanisms among genes. Reverse engineering the functional relevance of genes to specific cellular pathways and vice versa, through the exploitation of the inner structure of the ontological vocabularies, may help impart insight regarding the identification and prioritization of the critical role of specific genes. The proposed graph-theoretical method is showcased in a pancreatic cancer and a T-cell acute lymphoblastic leukemia gene set, incorporating edge and Resnik semantic similarity metrics, and systematically evaluated regarding its performance.
Keywords :
cancer; cellular biophysics; genomics; graph theory; molecular biophysics; reverse engineering; GOrevenge; Resnik semantic similarity metrics; T-cell acute lymphoblastic leukemia gene set; cellular pathway; critical molecular players; gene ontology; generic reverse engineering method; genomes; graph-theoretical method; hidden regulatory mechanism; inner structure; ontological vocabulary; pancreatic cancer; probed disease; Bioinformatics; Biological information theory; Cancer; Databases; Measurement; Ontologies; Bioinformatics; molecular network analysis; ontological analysis; semantic similarity; systems biology; Algorithms; Computational Biology; Databases, Genetic; Gene Regulatory Networks; Humans; Pancreatic Neoplasms; Precursor T-Cell Lymphoblastic Leukemia-Lymphoma; ROC Curve; Reproducibility of Results; Semantics;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2011.2164794