Abstract
BackgroundCervical cancers are ranked the second-most hazardous ailments among women worldwide. In the past two decades, microarray technologies have been applied to study genes involved in malignancy progress. However, in most of the published microarray studies, only a few genes were reported leaving rather a large amount of data unused. Also, RNA-Seq data has become more standard for transcriptome analysis and is widely applied in cancer studies. There is a growing demand for a tool to help the experimental researchers who are keen to explore cervical cancer gene therapy, but lack computer expertise to access and analyze the high throughput gene expression data.DescriptionThe dbCerEx database is designed to retrieve and process gene expression data from cervical cancer samples. It includes the genome wide expression profiles of cervical cancer samples, as well as a web utility to cluster genes with similar expression patterns. This feature will help researchers conduct further research to uncover novel gene functions.ConclusionThe dbCerEx database is freely available for non-commercial use at http://128.135.207.10/dbCerEx/, and will be updated and integrated with more features as needed.
Highlights
Cervical cancers account for the second-most gynecological cancer death cases worldwide, and this situation is worse in developing countries due to the lack of adequate organized screening programs
The dbCerEx database is freely available for non-commercial use at http://128.135.207.10/dbCerEx/, and will be updated and integrated with more features as needed
It is believed that Human Papilloma Virus (HPV) infections are the major causes of invasive cervical cancer [1]
Summary
Cervical cancers account for the second-most gynecological cancer death cases worldwide, and this situation is worse in developing countries due to the lack of adequate organized screening programs. Since 1997, the number of published results based on an analysis of gene expression microarray data has grown from 30 to over 5,000 publications per year [2]. Archival RNA samples of 25 patients were hybridized to Stanford microarray chips to build a seven gene scoring system [4]. This gene expression pattern could help to identify patients with cervical cancer who can be treated with radiotherapy alone. The specific expression profiles of candidate genes were selected to identify historical subtypes of cervical cancer [5]. RNA-Seq data has become more standard for transcriptome analysis and is widely applied in cancer studies. If one novel gene of interest has a correlated (positive or negative) expression pattern with an apoptosis-related gene, it indicates that they may share the same regulatory mechanism, which could provide the potential research proposal for the novel gene
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
