ArticleDatabase : the journal of biological databases and curation2014
RLIMS-P: an online text-mining tool for literature-based extraction of protein phosphorylation information.
Article in Database : the journal of biological databases and curation, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 23 citations in OpenAlex.
- GenPTM: A Generalizable Framework for Protein Post-Translational Modification Information Extraction from the Scientific Literature.Research square · 2026Article
- Using phosphoproteomics data to understand cellular signaling: a comprehensive guide to bioinformatics resources.Clinical proteomics · 2020Review
- Automated, Efficient, and Accelerated Knowledge Modeling of the Cognitive Neuroimaging Literature Using the ATHENA Toolkit.Frontiers in neuroscience · 2019Article
- iPTMnet: an integrated resource for protein post-translational modification network discovery.Nucleic acids research · 2018Article
- Analysis of Protein Phosphorylation and Its Functional Impact on Protein-Protein Interactions via Text Mining of the Scientific Literature.Methods in molecular biology (Clifton, N.J.) · 2017Article
- miRiaD: A Text Mining Tool for Detecting Associations of microRNAs with Diseases.Journal of biomedical semantics · 2016Article
- Mining clinical attributes of genomic variants through assisted literature curation in Egas.Database : the journal of biological databases and curation · 2016Article
- Building a glaucoma interaction network using a text mining approach.BioData mining · 2016Article
- Predicting CK2 beta-dependent substrates using linear patterns.Biochemistry and biophysics reports · 2015Article
- Article
- The BioGRID interaction database: 2015 update.Nucleic acids research · 2015Article
- pGenN, a gene normalization tool for plant genes and proteins in scientific literature.PloS one · 2015Article
- Construction of phosphorylation interaction networks by text mining of full-length articles using the eFIP system.Database : the journal of biological databases and curation · 2015Article
- Scaling drug indication curation through crowdsourcing.Database : the journal of biological databases and curation · 2015Article
- RLIMS-P 2.0: A Generalizable Rule-Based Information Extraction System for Literature Mining of Protein Phosphorylation Information.IEEE/ACM transactions on computational biology and bioinformaticsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 5 institutions in 2 countries.
Funding
Abstract
Protein phosphorylation is central to the regulation of most aspects of cell function. Given its importance, it has been the subject of active research as well as the focus of curation in several biological databases. We have developed Rule-based Literature Mining System for protein Phosphorylation (RLIMS-P), an online text-mining tool to help curators identify biomedical research articles relevant to protein phosphorylation. The tool presents information on protein kinases, substrates and phosphorylation sites automatically extracted from the biomedical literature. The utility of the RLIMS-P Web site has been evaluated by curators from Phospho.ELM, PhosphoGRID/BioGrid and Protein Ontology as part of the BioCreative IV user interactive task (IAT). The system achieved F-scores of 0.76, 0.88 and 0.92 for the extraction of kinase, substrate and phosphorylation sites, respectively, and a precision of 0.88 in the retrieval of relevant phosphorylation literature. The system also received highly favorable feedback from the curators in a user survey. Based on the curators' suggestions, the Web site has been enhanced to improve its usability. In the RLIMS-P Web site, phosphorylation information can be retrieved by PubMed IDs or keywords, with an option for selecting targeted species. The result page displays a sortable table with phosphorylation information. The text evidence page displays the abstract with color-coded entity mentions and includes links to UniProtKB entries via normalization, i.e., the linking of entity mentions to database identifiers, facilitated by the GenNorm tool and by the links to the bibliography in UniProt. Log in and editing capabilities are offered to any user interested in contributing to the validation of RLIMS-P results. Retrieved phosphorylation information can also be downloaded in CSV format and the text evidence in the BioC format. RLIMS-P is freely available. DATABASE URL: http://www.proteininformationresource.org/rlimsp/
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.