ReviewJournal of lipid research2009
A systems-based framework for understanding complex metabolic and cardiovascular disorders.
Review in Journal of lipid research, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Cardioinformatics: the nexus of bioinformatics and precision cardiology.Briefings in bioinformatics · 2020Article
- Relevance of Multi-Omics Studies in Cardiovascular Diseases.Frontiers in cardiovascular medicine · 2019Review
- A Network-Biology Informed Computational Drug Repositioning Strategy to Target Disease Risk Trajectories and Comorbidities of Peripheral Artery Disease.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2018Article
- An update on clonality: what smooth muscle cell type makes up the atherosclerotic plaque?F1000Research · 2018Review
- The genetic basis of peripheral arterial disease: current knowledge, challenges, and future directions.Circulation research · 2015Review
- Designing phenotyping studies for genetically engineered mice.Veterinary pathology · 2012Review
- MicroRNAs--regulators of signaling networks in dilated cardiomyopathy.Journal of cardiovascular translational research · 2010Review
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
Common forms of metabolic and cardiovascular diseases involve the interplay of numerous genes as well as important environmental factors. Traditional biochemical and genetic approaches generally attempt to dissect these diseases one gene at a time, for example, by analysis of Mendelian forms or genetically engineered experimental organisms. But, it is also important to understand how the genes interact with each other and the environment, and how these interactions change in disease states. Technological advances, such as the development of expression arrays that allow quantification of all transcript levels in a cell or tissue, have made it feasible to globally monitor molecular phenotypes that underlie disease states. By applying statistical methods, relationships between DNA variation, gene expression patterns, and diseases can be modeled.
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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.