Social pathway annotation: extensions of the systems biology metabolic modelling assistant

Abstract

High-throughput experiments have produced large amounts of heterogeneous data in the life sciences. These data are usually represented in different formats (and sometimes in technical documents) on the Web. Inevitably, life science researchers have to deal with all these data and different formats to perform their daily research, but it is simply not possible for a single human mind to analyse all these data. The integration of data in the life sciences is a key component in the analysis of biological processes. These data may contain errors, but the curation of the vast amount of data generated in the 'omic' era cannot be done by individual researchers. To address this problem, community-driven tools could be used to assist with data analysis. In this article, we focus on a tool with social networking capabilities built on top of the SBMM (Systems Biology Metabolic Modelling) Assistant to enable the collaborative improvement of metabolic pathway models (the application is freely available at http://sbmm.uma.es/SPA).

Role of a Web-based Software Platform for Systems Biology

“…In this way, a collaboration framework enlightens curation, annotation and database enrichment with regard to models and pathways. These are examples of existing frameworks: Bionumbers [61], SBMM [62], GARNET [63], Patika [64], Payao [65], Quail Genomics [66], PMI [67], Rapyd [68], DC pathway [69], InnateDB [70].…”