%0 Journal Article
%T Stringent response of Escherichia coli: revisiting the bibliome using literature mining
%A S¨®nia Carneiro
%A An¨¢lia Louren£¿o
%A Eug¨¦nio C Ferreira
%A Isabel Rocha
%J Microbial Informatics and Experimentation
%D 2011
%I BioMed Central
%R 10.1186/2042-5783-1-14
%X In this work, we review literature reports on the study of the stringent response in Escherichia coli. Rather than undertaking the development of a highly specialised literature mining approach, we investigate the suitability of concept recognition and statistical analysis of concept occurrence as means to highlight the concepts that are most likely to be biologically engaged during this response. The co-occurrence analysis of core concepts in this stringent response, i.e. the (p)ppGpp nucleotides with gene products was also inspected and suggest that besides the enzymes RelA and SpoT that control the basal levels of (p)ppGpp nucleotides, many other proteins have a key role in this response. Functional enrichment analysis revealed that basic cellular processes such as metabolism, transcriptional and translational regulation are central, but other stress-associated responses might be elicited during the stringent response. In addition, the identification of less annotated concepts revealed that some (p)ppGpp-induced functional activities are still overlooked in most reviews.In this paper we applied a literature mining approach that offers a more comprehensive analysis of the stringent response in E. coli. The compilation of relevant biological entities to this stress response and the assessment of their functional roles provided a more systematic understanding of this cellular response. Overlooked regulatory entities, such as transcriptional regulators, were found to play a role in this stress response. Moreover, the involvement of other stress-associated concepts demonstrates the complexity of this cellular response.Scientific literature represents a valuable source of biological information, in particular on the description of biological entities that we can find in a cellular system and how they are related to each other. To identify references to these entities in texts, here designated as biological concepts, literature mining approaches can be applied. Lately,
%U http://www.microbialinformaticsj.com/content/1/1/14