Array2GO: a simple web-based tool to search gene ontology for analysis of multi genes expression

作者：Kim Jun Sub; Kim Seung Jun; Lee Seung Yong; Han Jeong; An Yu Ri; Kim A Rang; Hwang Seung Yong^*

来源：BioChip Journal, 2010, 4(4): 329-335.

DOI：10.1007/s13206-010-4410-7

• Gene Ontology
• Omics
• Microarray
• Database
• Visualization

As a result of population and universality in high-throughput omics technologies in the last decade, such as microarray methods, many researchers who study their genes of interest that are similarly or differently expressed in cellular states, diseases, functional, or environmental element conditions have been possessed of the ability to identify biological validation on the genomic scale. In parallel with the advancement of omics experiments, the number of biological databases, which contain the biological annotations, genetic functionalities, metabolic pathways, and mutational information or functional interactions between genes or proteins, has increased. Fortunately, these datasets have been mainly opened to computational network protocols, such as FTP or SSH, and have freely served as web search tools to enable users to retrieve a biological annotation with queries. Of these databases, GO (Gene Ontology) provides controlled vocabulary terms for describing biological annotation of a gene or gene product in tree aspects that are classified as biological process, cellular component, and molecular function across various species. Also, GO gives researchers a publicly accessible tool for identification of a gene or gene product with GO terms. The result of this tool displays the hierarchical tree-type html format or DAGs (Directed Acyclic Graphs) graph-type format to users according to the three aspects of GO. However, as this permits users to ask only one keyword at a time, it is difficult to search many interesting gene sets in gene expression profiles obtained from microarray experiments at once. A few GO search tools have been developed to help in analysis of GO annotation for multi genes. However they have not satisfied user demands in terms of the simplicity of the user interface and visualization of analysis results. For these reasons, Array2GO, which has been based on a web environment, has been developed and is freely accessible at http://www.koreagene.co.kr/cgi-bin/service/servicel.pl.

• 出版日期2010-12-20