Before revision:  Hence the development of novel methodologies that can automatically analyze textual sources, extract facts and knowledge, and produce summarized representations that capture the most relevant information is a timely and pressing need. We present INtERAcT, a novel approach to infer interactions between molecular entities extracted from literature using an unsupervised procedure that takes advantage of recent developments in automatic text mining and text analysis.
After revision:  Here we present INtERAcT, a novel approach to infer interactions between molecular entities extracted from literature using an unsupervised procedure that takes advantage of recent developments in automatic text mining and text analysis.