ArticleBMC bioinformatics2008
OpenDMAP: an open source, ontology-driven concept analysis engine, with applications to capturing knowledge regarding protein transport, protein interactions and cell-type-specific gene expression.
Article in BMC bioinformatics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 1 of them a synthesis that pooled it.
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
50 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Combining entity co-occurrence with specialized word embeddings to measure entity relation in Alzheimer's disease.BMC medical informatics and decision making · 2019Article
- Differential gene expression in disease: a comparison between high-throughput studies and the literature.BMC medical genomics · 2017Article
- AtPID: a genome-scale resource for genotype-phenotype associations in Arabidopsis.Nucleic acids research · 2017Article
- BELMiner: adapting a rule-based relation extraction system to extract biological expression language statements from bio-medical literature evidence sentences.Database : the journal of biological databases and curation · 2017Article
- Knowledge Author: facilitating user-driven, domain content development to support clinical information extraction.Journal of biomedical semantics · 2016Article
- Is the crowd better as an assistant or a replacement in ontology engineering? An exploration through the lens of the Gene Ontology.Journal of biomedical informatics · 2016Article
- The role of ontologies in biological and biomedical research: a functional perspective.Briefings in bioinformatics · 2015Article
- SimConcept: a hybrid approach for simplifying composite named entities in biomedical text.IEEE journal of biomedical and health informatics · 2015Article
- KnowLife: a versatile approach for constructing a large knowledge graph for biomedical sciences.BMC bioinformatics · 2015Article
- Using the wisdom of the crowds to find critical errors in biomedical ontologies: a study of SNOMED CT.Journal of the American Medical Informatics Association : JAMIA · 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
- A generalizable NLP framework for fast development of pattern-based biomedical relation extraction systems.BMC bioinformatics · 2014Article
- Large-scale biomedical concept recognition: an evaluation of current automatic annotators and their parameters.BMC bioinformatics · 2014Article
- Thematic series on biomedical ontologies in JBMS: challenges and new directions.Journal of biomedical semantics · 2014Review
- Graph theory enables drug repurposing--how a mathematical model can drive the discovery of hidden mechanisms of action.PloS one · 2014Article
- Chapter 16: text mining for translational bioinformatics.PLoS computational biology · 2013Article
- Preliminary evaluation of the CellFinder literature curation pipeline for gene expression in kidney cells and anatomical parts.Database : the journal of biological databases and curation · 2013Article
- PIMiner: a web tool for extraction of protein interactions from biomedical literature.International journal of data mining and bioinformatics · 2013Article
- Representing annotation compositionality and provenance for the Semantic Web.Journal of biomedical semantics · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundInformation extraction (IE) efforts are widely acknowledged to be important in harnessing the rapid advance of biomedical knowledge, particularly in areas where important factual information is published in a diverse literature. Here we report on the design, implementation and several evaluations of OpenDMAP, an ontology-driven, integrated concept analysis system. It significantly advances the state of the art in information extraction by leveraging knowledge in ontological resources, integrating diverse text processing applications, and using an expanded pattern language that allows the mixing of syntactic and semantic elements and variable ordering.
resultsOpenDMAP information extraction systems were produced for extracting protein transport assertions (transport), protein-protein interaction assertions (interaction) and assertions that a gene is expressed in a cell type (expression). Evaluations were performed on each system, resulting in F-scores ranging from .26-.72 (precision .39-.85, recall .16-.85). Additionally, each of these systems was run over all abstracts in MEDLINE, producing a total of 72,460 transport instances, 265,795 interaction instances and 176,153 expression instances.
conclusionOpenDMAP advances the performance standards for extracting protein-protein interaction predications from the full texts of biomedical research articles. Furthermore, this level of performance appears to generalize to other information extraction tasks, including extracting information about predicates of more than two arguments. The output of the information extraction system is always constructed from elements of an ontology, ensuring that the knowledge representation is grounded with respect to a carefully constructed model of reality. The results of these efforts can be used to increase the efficiency of manual curation efforts and to provide additional features in systems that integrate multiple sources for information extraction. The open source OpenDMAP code library is freely available at http://bionlp.sourceforge.net/
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.