A user-friendly web application that contains ready-for-simulation versions of the BioModels Database, and allows for the intuitive creation of new models. Experimental biologist and students of bioinformatics or systems biology without programming skills can easily use it. Expert users can quickly implement basic models and downloading the code for further tailoring.
MetReS (Metabolic Reconstruction Server) is a genomic database that is shared between two software applications that address important biological problems. Biblio-MetReS is a data-mining tool that enables the reconstruction of molecular networks based on automated text-mining analysis of published scientific literature. Homol-MetReS allows functional (re)annotation of proteomes, to properly identify both the individual proteins involved in the processes of interest and their function.
Presents a valid alternative for automated annotation of chemical entities in biomedical documents. The individual performance of CheNER could be further improved by expanding the dictionaries of chemical entities used in its training. In addition, CheNER may provide a valuable resource to automatically derive new features that could be used for training and improving the performance of newer methods for tagging chemical entities.
CheNER: chemical named entity recognizer. Usié A, Alves R, Solsona F, Vázquez M, Valencia A. Bioinformatics. 2014 Apr 1;30(7):1039-40. doi: 10.1093/bioinformatics/btt639. Epub 2013 Nov 13.