This paper in Nature from Ian Taylor and Jeff Wrana from U. Toronto present a compelling method for the discrimination and diagnosis of disease states based on the disruption of co-expression patterns with neighbors in a protein interaction network. Typically, the search for cancer biomarkers involves searching for differentially expressed genes which alone can discriminate between different cancer diagnoses. The authors present a method which integrates co-expression and public protein interaction information to show that genes whose protein network neighbors become dysregulated may be used to predict breast cancer outcomes. Their findings support the emerging notion that biomarkers might be improved by focusing on pathways rather than single genes alone. A couple of recent papers from our lab indicate show early signs of promise in this regard. Their results have implications for the systematic discovery of markers in a variety of diseases.
Systems Biology is changing the way biology is done. Is it a fad or is it effective? This blog tracks current happenings and helps you stay on top of the field. You can find a list of relevant papers at systems biology paper watch Have you heard a talk or read a paper in bioinformatics / systems biology you would like to tell other people about? Email: email@example.com and get the word out!