ReviewGenome biology2013
Toward knowledge support for analysis and interpretation of complex traits.
Review in Genome biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Combining lexical and context features for automatic ontology extension.Journal of biomedical semantics · 2020Article
- The anatomy of phenotype ontologies: principles, properties and applications.Briefings in bioinformatics · 2018Article
- The digital revolution in phenotyping.Briefings in bioinformatics · 2016Article
- Concept selection for phenotypes and diseases using learn to rank.Journal of biomedical semantics · 2015Article
- PhenoMiner: from text to a database of phenotypes associated with OMIM diseases.Database : the journal of biological databases and curation · 2015Article
- Phenotype ontologies and cross-species analysis for translational research.PLoS genetics · 2014Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The systematic description of complex traits, from the organism to the cellular level, is important for hypothesis generation about underlying disease mechanisms. We discuss how intelligent algorithms might provide support, leading to faster throughput.
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.