Đang chuẩn bị liên kết để tải về tài liệu:
Báo cáo y học: "A human functional protein interaction network and its application to cancer data analysis"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Wertheim cung cấp cho các bạn kiến thức về ngành y đề tài: A human functional protein interaction network and its application to cancer data analysis. | Wu et al. Genome Biology 2010 11 R53 http genomebiology.eom 2010 11 5 R53 w Genome Biology RESEARCH _ Open Access A human functional protein interaction network and its application to cancer data analysis Guanming Wu 1 Xin Feng2 3 and Lincoln Stein1 2 Abstract Background One challenge facing biologists is to tease out useful information from massive data sets for further analysis. A pathway-based analysis may shed light by projecting candidate genes onto protein functional relationship networks. We are building such a pathway-based analysis system. Results We have constructed a protein functional interaction network by extending curated pathways with noncurated sources of information including protein-protein interactions gene coexpression protein domain interaction Gene Ontology GO annotations and text-mined protein interactions which cover close to 50 of the human proteome. By applying this network to two glioblastoma multiforme GBM data sets and projecting cancer candidate genes onto the network we found that the majority of GBM candidate genes form a cluster and are closer than expected by chance and the majority of GBM samples have sequence-altered genes in two network modules one mainly comprising genes whose products are localized in the cytoplasm and plasma membrane and another comprising gene products in the nucleus. Both modules are highly enriched in known oncogenes tumor suppressors and genes involved in signal transduction. Similar network patterns were also found in breast colorectal and pancreatic cancers. Conclusions We have built a highly reliable functional interaction network upon expert-curated pathways and applied this network to the analysis of two genome-wide GBM and several other cancer data sets. The network patterns revealed from our results suggest common mechanisms in the cancer biology. Our system should provide a foundation for a network or pathway-based analysis platform for cancer and other diseases. Background High-throughput .