ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2009
Semantic relations for interpreting DNA microarray data.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Integration of data from omic studies with the literature-based discovery towards identification of novel treatments for neovascularization in diabetic retinopathy.BioMed research international · 2013Pooled it
- Context-driven automatic subgraph creation for literature-based discovery.Journal of biomedical informatics · 2015Article
- Networks of neuroinjury semantic predications to identify biomarkers for mild traumatic brain injury.Journal of biomedical semantics · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The results from microarray experiments, in the form of lists of over- and under-expressed genes, have great potential to support progress in biomedical research. However, results are not easy to interpret. Information about the function of the genes and their relation to other genes is needed, and this information is usually present in vast amounts of biomedical literature. Considerable effort is required to find, read and extract relevant information from the literature. A potential solution is to use computerized text analysis methods to extract relevant information. Our proposal enhances current methods in this regard and uses semantic relations extracted from biomedical text with the SemRep information extraction system. We describe an application that integrates microarray results with semantic relations and discuss its benefits in supporting enhanced access to the relevant literature for interpretation of results.
Indexed as
Identifiers
20351860PMC2815475What 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.