Using the protein interaction network to predict protein folds without homology
نویسندگان
چکیده
منابع مشابه
Using the Protein-protein Interaction Network to Identifying the Biomarkers in Evolution of the Oocyte
Background Oocyte maturity includes nuclear and cytoplasmic maturity, both of which are important for embryo fertilization. The development of oocyte is not limited to the period of follicular growth, and starts from the embryonic period and continues throughout life. In this study, for the purpose of evaluating the effect of the FSH hormone on the expression of genes, GEO access codes for this...
متن کاملPrediction of Protein Sub-Mitochondria Locations Using Protein Interaction Networks
Background: Prediction of the protein localization is among the most important issues in the bioinformatics that is used for the prediction of the proteins in the cells and organelles such as mitochondria. In this study, several machine learning algorithms are applied for the prediction of the intracellular protein locations. These algorithms use the features extracted from pro...
متن کاملThe phox homology (PX) domain protein interaction network in yeast.
The phox homology (PX) domain is a phosphoinositide-binding domain that is conserved from yeast to human. Here we show for the first time by genome-wide two-hybrid screens and in vitro binding assays that the PX domain is a bona fide protein interaction domain. The yeast PX domain-only proteins Grd19p (YOR357C) and Ypt35p (YHR105W), as well as the isolated PX domains from Mvp1p (YMR004W), Snx42...
متن کاملprotein-protein interaction network analysis of cirrhosis liver disease
aim : evaluation of biological characteristics of 13 identified proteins of patients with cirrhotic liver disease is the main aim of this research. background : in clinical usage, liver biopsy remains the gold standard for diagnosis of hepatic fibrosis. evaluation and confirmation of liver fibrosis stages and severity of chronic diseases require a precise and noninvasive biomarkers. since the...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: BMC Systems Biology
سال: 2007
ISSN: 1752-0509
DOI: 10.1186/1752-0509-1-s1-p69