ArticleSummit on translational bioinformatics2008
Ontology-anchored Approaches to Conceptual Knowledge Discovery in a Multi-dimensional Research Data Repository.
Article in Summit on translational bioinformatics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 12 citations in OpenAlex.
- Scientist and data architect collaborate to curate and archive an inner ear electrophysiology data collection.PloS one · 2019Article
- Computational framework to support integration of biomolecular and clinical data within a translational approach.BMC bioinformatics · 2013Article
- k-Neighborhood decentralization: a comprehensive solution to index the UMLS for large scale knowledge discovery.Journal of biomedical informatics · 2012Article
- Research-IQ: development and evaluation of an ontology-anchored integrative query tool.Journal of biomedical informatics · 2011Article
- The TOKEn project: knowledge synthesis for in silico science.Journal of the American Medical Informatics Association : JAMIA · 2011Article
- Pediatric diabetes registries: when baby steps are not enough.Journal of diabetes science and technology · 2011Article
- Multi-dimensional discovery of biomarker and phenotype complexes.BMC bioinformatics · 2010Article
- Conceptual dissonance: evaluating the efficacy of natural language processing techniques for validating translational knowledge constructs.Summit on translational bioinformatics · 2009Article
- Supporting the design of translational clinical studies through the generation and verification of conceptual knowledge-anchored hypotheses.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2008Article
- Applying knowledge-anchored hypothesis discovery methods to advance clinical and translational research: the OAMiner project.Journal of the American Medical Informatics Association : JAMIAArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Chronic Lymphocytic Leukemia (CLL) is the most common adult leukemia in the U.S., and is currently incurable. Though a small number of biomarkers that may correlate to risk of disease progression or treatment outcome in CLL have been discovered, few have been validated in prospective studies or adopted in clinical practice. In order to address this gap in knowledge, it is desirable to discover and test hypotheses that are concerned with translational biomarker-to-phenotype correlations. We report upon a study in which commonly available ontologies were utilized to support the discovery of such translational correlations. We have specifically applied a technique known as constructive induction to reason over the contents of a research data repository utilized by the NCI-funded CLL Research Consortium. Our findings indicate that such an approach can produce semantically meaningful results that can inform hypotheses about higher-level relationships between the types of data contained in such a repository.
Identifiers
21347129PMC3041525W320807751What 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.