An integrated computational proteomics method to extract protein targets for Fanconi Anemia studies
Proceedings of the 2006 ACM symposium on Applied computing
A case study of integrating protein interaction data using semantic web technology
International Journal of Bioinformatics Research and Applications
Towards an integrative human pathway database for systems biology applications
Proceedings of the 2008 ACM symposium on Applied computing
IMPRECO: Distributed prediction of protein complexes
Future Generation Computer Systems
Computers in Biology and Medicine
Protein-to-protein interactions: Technologies, databases, and algorithms
ACM Computing Surveys (CSUR)
Predicting protein-protein interactions with k-nearest neighbors classification algorithm
CIBB'09 Proceedings of the 6th international conference on Computational intelligence methods for bioinformatics and biostatistics
Mining protein interactions from text using convolution kernels
PAKDD'09 Proceedings of the 13th Pacific-Asia international conference on Knowledge discovery and data mining: new frontiers in applied data mining
Detecting disease genes based on semi-supervised learning and protein-protein interaction networks
Artificial Intelligence in Medicine
Web service for predicting interacting proteins and application to human and HIV-1 proteins
ICIC'06 Proceedings of the 2006 international conference on Computational Intelligence and Bioinformatics - Volume Part III
Tutorial on biological networks
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
| Hi-index | 3.84 |
Motivation: High-throughput experiments are being performed at an ever-increasing rate to systematically elucidate protein--protein interaction (PPI) networks for model organisms, while the complexities of higher eukaryotes have prevented these experiments for humans. Results: The Online Predicted Human Interaction Database (OPHID) is a web-based database of predicted interactions between human proteins. It combines the literature-derived human PPI from BIND, HPRD and MINT, with predictions made from Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster and Mus musculus. The 23 889 predicted interactions currently listed in OPHID are evaluated using protein domains, gene co-expression and Gene Ontology terms. OPHID can be queried using single or multiple IDs and results can be visualized using our custom graph visualization program. Availability: Freely available to academic users at http://ophid.utoronto.ca, both in tab-delimited and PSI-MI formats. Commercial users, please contact I.J. Contact: juris@ai.utoronto.ca Supplementary information: http://ophid.utoronto.ca/supplInfo.pdf