ReviewJournal of diabetes science and technology2009
Technologies for diabetes genomics.
Review in Journal of diabetes science and technology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed, 3 citations in OpenAlex.
- The personalized medicine for diabetes meeting summary report.Journal of diabetes science and technology · 2009Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The genetic risk for diabetes largely depends on the type of diabetes and the penetrance and severity of the effect of the contributing genes. This ranges from the high-risk mutations of neonatal diabetes and maturityonset diabetes of the young to the lower, but still significant, risk conferred by common human leukocyte antigen alleles in type 1 diabetes to the still-lower risk conferred by the common variants associated with type 2 diabetes. There are many new molecular technologies, each with their own set of methodological issues, that have been used for genome-wide association studies and that can be used for determining the genetic risk for these various types of diabetes. These technologies include whole genome single nucleotide polymorphism microarrays, high-throughput polymorphism analyzers, next-generation sequencers, and copy-number variant technologies.
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.