Text mining for metabolic pathways, signaling cascades, and protein networks. Export

@article{citeulike:227671, abstract = {The complexity of the information stored in databases and publications on metabolic and signaling pathways, the high throughput of experimental data, and the growing number of publications make it imperative to provide systems to help the researcher navigate through these interrelated information resources. Text-mining methods have started to play a key role in the creation and maintenance of links between the information stored in biological databases and its original sources in the literature. These links will be extremely useful for database updating and curation, especially if a number of technical problems can be solved satisfactorily, including the identification of protein and gene names (entities in general) and the characterization of their types of interactions. The first generation of openly accessible text-mining systems, such as iHOP (Information Hyperlinked over Proteins), provides additional functions to facilitate the reconstruction of protein interaction networks, combine database and text information, and support the scientist in the formulation of novel hypotheses. The next challenge is the generation of comprehensive information regarding the general function of signaling pathways and protein interaction networks.}, address = {National Center for Biotechnology, CNB-CSIC, Darwin 3, Cantoblanco, 28049 Madrid, Spain.}, author = {Hoffmann, R. and Krallinger, M. and Andres, E. and Tamames, J. and Blaschke, C. and Valencia, A.}, citeulike-article-id = {227671}, citeulike-linkout-0 = {http://dx.doi.org/10.1126/stke.2832005pe21}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/15886388}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=15886388}, day = {10}, doi = {10.1126/stke.2832005pe21}, issn = {1525-8882}, journal = {Sci STKE}, keywords = {analysis, text}, month = {May}, number = {283}, posted-at = {2005-06-14 21:24:25}, priority = {2}, title = {Text mining for metabolic pathways, signaling cascades, and protein networks.}, url = {http://dx.doi.org/10.1126/stke.2832005pe21}, volume = {2005}, year = {2005} }

TY - JOUR ID - citeulike:227671 L3 - citeulike-article-id:227671 N2 - The complexity of the information stored in databases and publications on metabolic and signaling pathways, the high throughput of experimental data, and the growing number of publications make it imperative to provide systems to help the researcher navigate through these interrelated information resources. Text-mining methods have started to play a key role in the creation and maintenance of links between the information stored in biological databases and its original sources in the literature. These links will be extremely useful for database updating and curation, especially if a number of technical problems can be solved satisfactorily, including the identification of protein and gene names (entities in general) and the characterization of their types of interactions. The first generation of openly accessible text-mining systems, such as iHOP (Information Hyperlinked over Proteins), provides additional functions to facilitate the reconstruction of protein interaction networks, combine database and text information, and support the scientist in the formulation of novel hypotheses. The next challenge is the generation of comprehensive information regarding the general function of signaling pathways and protein interaction networks. IS - 283 JF - Sci STKE SN - 1525-8882 AD - National Center for Biotechnology, CNB-CSIC, Darwin 3, Cantoblanco, 28049 Madrid, Spain. TI - Text mining for metabolic pathways, signaling cascades, and protein networks. VL - 2005 KW - analysis KW - text AU - Hoffmann, R AU - Krallinger, M AU - Andres, E AU - Tamames, J AU - Blaschke, C AU - Valencia, A PY - 2005/05/10/ UR - http://dx.doi.org/10.1126/stke.2832005pe21 ER -