Title :
Semi-automated microRNA ontology development based on artificial neural networks
Author :
Jingshan Huang ; Jiangbo Dang ; Xingyu Lu ; Min Xiong ; Gerthoffer, William T. ; Ming Tan
Author_Institution :
Sch. of Comput., Univ. of South Alabama, Mobile, AL, USA
Abstract :
microRNAs (miRNAs) are special non-coding RNAs that perform important roles through their target genes. Biologists´ conventional miRNA knowledge discovery is time-consuming, labor-intensive, and error-prone. Semantic technologies, which are created upon domain ontologies, can greatly enhance miRNA knowledge discovery. Unfortunately, yet no specific miRNA domain ontologies currently exist. It thus motivates the construction of a miRNA ontology. In addition, a manual ontology development has many drawbacks. We present in this paper a semi-automated ontology development methodology. The developed ontology is the very first one of its kind that formally encodes miRNA domain knowledge. It aims to provide data exchange standards and common data elements and thus help identify novel data connections among heterogeneous sources.
Keywords :
RNA; biology computing; data mining; genetics; molecular biophysics; neural nets; ontologies (artificial intelligence); artificial neural networks; biologist conventional miRNA knowledge discovery; data elements; data exchange; domain ontologies; encodes miRNA domain knowledge; heterogeneous sources; manual ontology development; noncoding RNA; semantic technologies; semiautomated microRNA ontology; semiautomated ontology development methodology; target genes; Biological information theory; Educational institutions; Electronic mail; Ontologies; Semantics; Training; Semi-automated ontology development; artificial neural networks; microRNA ontology;
Conference_Titel :
Bioinformatics and Biomedicine (BIBM), 2013 IEEE International Conference on
Conference_Location :
Shanghai
DOI :
10.1109/BIBM.2013.6732551
