Welcome to the web-site of the Computational Health Informatics (CHI) Laboratory in Reza Radiotherapy and Oncology Center. Our group consists of artificial intelligence and molecular genetics experts. We have been developing a novel computational biology and data mining algorithm to detect patterns and dependencies in large datasets from health informatics system in cancer research. With analyzing and comparing biological discoveries with existing guidelines, and feeding that information back to experts in order to detect cancer in early stages and improve accuracy of decisions in cancer treatment. The aim of this laboratory is applied new applications of machine learning and pattern recognition to improve health care output and quality of care among cancer patients.
The recent study at this laboratory in bioinformatics field is high throughput DNA methylation data analysis which was generated at RROC Computational Health Informatics (CHI) Laboratory in Iran. DNA methylation is an important regulator of gene transcription, and its role in carcinogenesis has been a topic of considerable interest in the last few years. Alterations in DNA methylation are common in a variety of tumors as well as in development. Of all epigenetic modifications, hypermethylation, which represses transcription of the promoter regions of tumor suppressor genes leading to gene silencing, has been most extensively studied. However, global hypomethylation has also been recognized as a cause of oncogenesis. As methylation occurs early and can be detected in body fluids, it may be of potential use in early detection of tumors and for determining the prognosis in cancer research.
The steps needed to prepare for a nuclear medicine scan depend on the type of test and the tissue that will be studied. Some scans require fasting for 2 to 12 hours before the test. For others, you may be asked to take a laxative or use an enema. Be sure your doctor or nurse knows everything you take, even over-the-counter drugs, vitamins, and herbs. You may need to avoid some medicines (prescription and over-the-counter) before the test.
Our bioinformatics group designed a useful tool (DMRFusion) for comprehensive DNA methylation analysis of differentially methylated regions (DMRs) on various type of methylation sequencing service data like as WGBS, RRBS and target-capture methods such as Agilent SureSelect methyl-seq.
DMRFusion is an R package for DNA methylation analysis, annotation and visualization for DMRs with a high fold difference score (p value and FDR less than 0.05 and type I error: 0.04) from high-throughput bisulfite sequencing.
|Goal||A tool to differentially methylated region detection based on the ranked fusion method|