Đang chuẩn bị liên kết để tải về tài liệu:
Báo cáo y học: "Insights gained from the reverse engineering of gene networks in keloid fibroblasts"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học quốc tế cung cấp cho các bạn kiến thức về ngành y đề tài: Insights gained from the reverse engineering of gene networks in keloid fibroblasts. | Ooi and Phan Theoretical Biology and Medical Modelling 2011 8 13 http www.tbiomed.eom content 8 1 13 THEORETICAL BIOLOGY AND MEDICAL MODELLING RESEARCH Open Access Insights gained from the reverse engineering of gene networks in keloid fibroblasts Brandon NS Ooi1 and Toan Thang Phan2 Correspondence nickooi@hotmail.com 1Graduate Programme in Bioengineering National University of Singapore Singapore Full list of author information is available at the end of the article 2 BioMed Central Abstract Background Keloids are protrusive claw-like scars that have a propensity to recur even after surgery and its molecular etiology remains elusive. The goal of reverse engineering is to infer gene networks from observational data thus providing insight into the inner workings of a cell. However most attempts at modeling biological networks have been done using simulated data. This study aims to highlight some of the issues involved in working with experimental data and at the same time gain some insights into the transcriptional regulatory mechanism present in keloid fibroblasts. Methods Microarray data from our previous study was combined with microarray data obtained from the literature as well as new microarray data generated by our group. For the physical approach we used the fREDUCE algorithm for correlating expression values to binding motifs. For the influence approach we compared the Bayesian algorithm BANJO with the information theoretic method ARACNE in terms of performance in recovering known influence networks obtained from the KEGG database. In addition we also compared the performance of different normalization methods as well as different types of gene networks. Results Using the physical approach we found consensus sequences that were active in the keloid condition as well as some sequences that were responsive to steroids a commonly used treatment for keloids. From the influence approach we found that BANJO was better at recovering the gene networks compared to .