CBD: a biomarker database for colorectal cancer

Abstract

Colorectal cancer (CRC) biomarker database (CBD) was established based on 870 identified CRC biomarkers and their relevant information from 1115 original articles in PubMed published from 1986 to 2017. In this version of the CBD, CRC biomarker data were collected, sorted, displayed and analysed. The CBD with the credible contents as a powerful and time-saving tool provide more comprehensive and accurate information for further CRC biomarker research. The CBD was constructed under MySQL server. HTML, PHP and JavaScript languages have been used to implement the web interface. The Apache was selected as HTTP server. All of these web operations were implemented under the Windows system. The CBD could provide to users the multiple individual biomarker information and categorized into the biological category, source and application of biomarkers; the experiment methods, results, authors and publication resources; the research region, the average age of cohort, gender, race, the number of tumours, tumour location and stage. We only collect data from the articles with clear and credible results to prove the biomarkers are useful in the diagnosis, treatment or prognosis of CRC. The CBD can also provide a professional platform to researchers who are interested in CRC research to communicate, exchange their research ideas and further design high-quality research in CRC. They can submit their new findings to our database via the submission page and communicate with us in the CBD.Database URL: http://sysbio.suda.edu.cn/CBD/

Publication
Database
Xueli Zhang
Xueli Zhang
PhD of Bioinformatics, Assistant Professor

My research interest is to explore the comorbidity relationship of diseases based on complex networks and to find new combination markers, and has constructed multiple biomarker databases and prediction models.

Qiliang Peng
Qiliang Peng
Resident Physician

My research interests primarily revolve around basic and clinical translational research in radiotherapy for malignant tumors, cancer biomarkers, and medical bioinformatics.