PIPs: human protein–protein interaction prediction database

نویسندگان

  • Mark D. McDowall
  • Michelle S. Scott
  • Geoffrey J. Barton
چکیده

The PIPs database (http://www.compbio.dundee.ac.uk/www-pips) is a resource for studying protein-protein interactions in human. It contains predictions of >37,000 high probability interactions of which >34,000 are not reported in the interaction databases HPRD, BIND, DIP or OPHID. The interactions in PIPs were calculated by a Bayesian method that combines information from expression, orthology, domain co-occurrence, post-translational modifications and sub-cellular location. The predictions also take account of the topology of the predicted interaction network. The web interface to PIPs ranks predictions according to their likelihood of interaction broken down by the contribution from each information source and with easy access to the evidence that supports each prediction. Where data exists in OPHID, HPRD, DIP or BIND for a protein pair this is also reported in the output tables returned by a search. A network browser is included to allow convenient browsing of the interaction network for any protein in the database. The PIPs database provides a new resource on protein-protein interactions in human that is straightforward to browse, or can be exploited completely, for interaction network modelling.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

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 کامل

Study 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 کامل

Construction 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 کامل

Discovering Domains Mediating Protein Interactions

Background: Protein-protein interactions do not provide any direct information re‌garding the domains within the proteins that mediate the interactions. The majority of proteins are multi domain proteins and the interaction between them is often defined by the pairs of their domains. Most of the former studies focus only on interacting do‌main pairs. However they do not consider the in...

متن کامل

Prediction of Coffee Effects in Rats with Healthy and NAFLD Conditions Based on Protein-Protein Interaction Network Analysis

Background and objectives: Non-alcoholic fatty liver disease (NAFLD) is a common liver condition. On the other hand, coffee consumption has shown promising for gastrointestinal diseases.  Detection of the most valuable biomarkers of decaffeinated coffee treatment in healthy and non-alcoholic fatty liver disease conditions was the aim of the present study. Methods:</stro...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره 37  شماره 

صفحات  -

تاریخ انتشار 2009