Title :
Biases in information content measurement of gene ontology terms
Author :
Milano, Michela ; Agapito, Giuseppe ; Guzzi, Pietro H. ; Cannataro, Mario
Author_Institution :
Dept. of Surg. & Med. Sci., Univ. of Catanzaro, Catanzaro, Italy
Abstract :
The Gene Ontology (GO) is used to achieve information about gene and protein functions by using a structured vocabulary of terms (GO Terms). GO Terms are related to biological concepts such as proteins or genes through the annotation process. There exist many different annotation processes identified by different evidence codes (EC). Annotated data are stored in public databases such as the Gene Ontology Annotation (GOA) database. Each term has a different specificity also referred to as Information Content (IC) of terms. Both the structure of GO and the corpora of annotation are continuously subject to change due to novel experimental findings. This process is often referred to as ontology evolution. This work focuses on how changes of annotations affect the IC of terms. The study confirms that statistically significant difference among many whole GOA versions exists on each species. Furthermore, there is also a statistically significant difference considering MF taxonomy for human, yeast, worm and fly. These results convey that annotation corpora changes have a high impact on IC.
Keywords :
bioinformatics; genetics; ontologies (artificial intelligence); proteins; Gene Ontology Annotation database; Information Content; biological concepts; evidence codes; gene function; gene ontology terms; information content measurement; protein function; specificity; Databases; Evolution (biology); Grippers; Integrated circuits; Manuals; Ontologies; Proteins; Gene Ontology; Information Bias; Information Content;
Conference_Titel :
Bioinformatics and Biomedicine (BIBM), 2014 IEEE International Conference on
Conference_Location :
Belfast
DOI :
10.1109/BIBM.2014.6999375