@article{
author = "Perović, Vladimir R. and Šumonja, Neven and Gemović, Branislava S. and Toska, Eneda and Roberts, Stefan G. E. and Veljković, Nevena V.",
year = "2017",
abstract = "The TRI_tool, a sequence-based web tool for prediction of protein interactions in the human transcriptional regulation, is intended for biomedical investigators who work on understanding the regulation of gene expression. It has an improved predictive performance due to the training on updated, human specific, experimentally validated datasets. The TRI_tool is designed to test up to 100 potential interactions with no time delay and to report both probabilities and binarized predictions.",
journal = "Bioinformatics",
title = "TRI_tool: a web-tool for prediction of protein-protein interactions in human transcriptional regulation",
volume = "33",
number = "2",
pages = "289-291",
doi = "10.1093/bioinformatics/btw590"
}