Dragon Extractor of Methylated Genes in Diseases  
How to use the system?

Dragon Extractor of Methylated Genes in Diseases can extract associations between methylated genes and diseases from text submitted by users. You can follow these steps in order to use the system:
Step 1: Provide text to the system. You can paste text in the text area provided on the home page or you can upload a ".txt" file that contains the text.
Step 2: Select the text format. The first format is PubMed Abstracts. The abstracts must be in "Abstract (Text)" format as specified by PubMed. Below is an example of an abstract in an "Abstract (Text)" format.

2. Adv Biomed Res. 2012;1:80. doi: 10.4103/2277-9175.102990. Epub 2012 Oct 31. Study of promoter methylation pattern of 14-3-3 sigma gene in normal and cancerous tissue of breast: A potential biomarker for detection of breast cancer in patients.

Gheibi A, Kazemi M, Baradaran A, Akbari M, Salehi M.

Department of Biomedical Sciences, Division of Genetics, Isfahan, Iran.

BACKGROUND: In recent years, DNA methylation as a main epigenetic modification in human cancer is found as a promising biomarker in early detection of breast cancer. Possible applications of numerous hypermethylated genes have been reported in diagnosis of breast cancer but there has been a little comprehensive study on the clinical usefulness of these genes in breast cancer. The aim of the present study was to investigate the promoter methylation status of 14-3-3 sigma gene with the goal of developing a diagnostic application in breast cancer. MATERIALS AND METHODS: Totally 40 cases of cancerous and noncancerous tissues were studied. DNA was extracted from tissue samples, and promoter methylation pattern was determined by using methylation-specific polymerase chain reaction. RESULTS: Methylation pattern of 14-3-3 sigma promoter significantly differed between control and malignant breast tissues (P = 0.001), and there was no remarkable correlation between methylation and age (P > 0.05). CONCLUSION: The relationship of promoter methylation of 14-3-3 sigma with development of breast cancer found in this study and confirmed the results of previous reports suggests that we can provide the foundation for possible application of 14-3-3 sigma as a potential biomarker for early detection and monitoring disease status.

PMID: 23326810 [PubMed]

If your text does not follow these specifications then choose Other Format.
Step 2: Click the Submit button. After the mining process is finished, a summary table and a full report will be available on the results page.

The summary table lists for each sentence genes, methylation words and diseases that appear in the sentence, The abstract where the sentence appears, and the sentence itself (see figure below).

Summary Table

The full report lists for each abstract genes, methylation words and diseases that appear in a sentence, the corresponding color-tagged sentence, and colored tagging of genes, diseases and methylation words that appear in the abstract (see figure below).

Full Report

If you want to try the system, but you do not have text, you can click the Sample Abstracts button on the text submission page. The system will process sample abstracts, and you will see the results.

Go to the home page to start using the system.

For any technical questions or comments, please contact: arwa.binres@kaust.edu.sa

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