ReviewNeuromolecular medicine2004
Gene expression profiling in neurological disorders: toward a systems-level understanding of the brain.
Review in Neuromolecular medicine, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 21 citations in OpenAlex.
- Microarray expression profiling in 6-hydroxydopamine-induced dopaminergic neuronal cell death.Journal of neural transmission (Vienna, Austria : 1996) · 2011Article
- Gene expression profiling of neurochemically defined regions of the human brain by in situ hybridization-guided laser capture microdissection.Journal of neuroscience methods · 2009Article
- Spatial mapping of protein abundances in the mouse brain by voxelation integrated with high-throughput liquid chromatography-mass spectrometry.Genome research · 2007Article
- High throughput protein expression screening in the nervous system--needs and limitations.The Journal of physiology · 2006Review
- Multiple sclerosis genetics: leaving no stone unturned.Genes and immunity · 2005Review
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
Neurological disease arises when a sufficient number of neural cells stop performing their normal functions, lose their ability to respond to local environment, and die. In the last decade, a major technological leap led to the development of efficient and cost-effective high-throughput methods for determining gene expression. This, in turn, resulted in the rapid accumulation of data describing gene expression patterns in the brain of humans and experimental animals. This article reviews several of the most commonly used technologies to retrieve transcriptional information, such as large-scale expressed sequence tag (EST) sequencing, serial analyses of gene experiment, and different DNA microarray platforms. In addition, efforts focusing on data collection, sharing, and standardization are described. A section is devoted to the latest advances in large-scale gene expression in several neurological disorders, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, and epilepsy. Finally, the need for integration of different sources of data is discussed in the context of systems biology and how such integration could result in improved diagnostics, therapies, and disease prevention.
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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.