Visualising protein interaction networks with power graphs
نویسندگان
چکیده
منابع مشابه
Prediction 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 کاملStudy of PKA binding sites in cAMP-signaling pathway using structural protein-protein interaction networks
Backgroud: Protein-protein interaction, plays a key role in signal transduction in signaling pathways. Different approaches are used for prediction of these interactions including experimental and computational approaches. In conventional node-edge protein-protein interaction networks, we can only see which proteins interact but ‘structural networks’ show us how these proteins inter...
متن کاملConstruction and Analysis of Tissue-Specific Protein-Protein Interaction Networks in Humans
We have studied the changes in protein-protein interaction network of 38 different tissues of the human body. 123 gene expression samples from these tissues were used to construct human protein-protein interaction network. This network is then pruned using the gene expression samples of each tissue to construct different protein-protein interaction networks corresponding to different studied ti...
متن کاملprotein-protein interaction networks (ppi) and complex diseases
normal 0 false false false en-us x-none ar-sa microsoftinternetexplorer4 the physical interaction of proteins which lead to compiling them into large densely connected networks is a noticeable subject to investigation. protein interaction networks are useful because of making basic scientific abstraction and improving biological and biomedical applications. based on principle roles of proteins ...
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-p51