ArticleSummit on translational bioinformatics2008
BioEMR: an integrative framework for cancer research with multiple genomic technologies.
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 3 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
3 citing papers in PubMed.
- Different Seasonal Variations of Potassium in Hemodialysis Patients with High Longitudinal Potassium Levels: A Multicenter Cohort Study Using DialysisNet.Yonsei medical journal · 2021Article
- Observational
- Development of korean rare disease knowledge base.Healthcare informatics research · 2012Article
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 rapid development of omic technologies facilitate cancer researchers to apply multiple genomic technologies simultaneously. In fact, the complex nature of cancer biology is the reason why we need tools for data integration. Given the complexity of managing multiple technologies and dataset formats, several projects have been introduced including cancer Biomedical Informatics Grid (caGRID) and the Biomedical Research Institute Domain Group (BRIDG) with limited applicability. We introduce an object-oriented data model, Cancer Genomics Object Model (CaGe-OM) for multiple genomics data and Xperanto-CaGe, a web-based application using CaGe-OM with hybrid object-relational mapping technique. The hybrid approach uses objectrelational mapping which is extended to include dynamic structure by using Entity-Attribute-Value (EAV) model. CaGe-OM and Xperanto-CaGe are an attempt to establish a comprehensive framework for integrated storage and interpretation of clinical and multiple genomics data and to facilitate model-level integration of other newly emerging data types. A pilot implementation for the integrated clinical, histo-pathological and genomic information systems is introduced.
Identifiers
21347128PMC3041523What 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.