ArticleBioinformatics (Oxford, England)2009
A tool for identification of genes expressed in patterns of interest using the Allen Brain Atlas.
Article in Bioinformatics (Oxford, England), 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- The PV2 cluster of parvalbumin neurons in the murine periaqueductal gray: connections and gene expression.Brain structure & function · 2022Article
- Article
- Systematic analysis of expression signatures of neuronal subpopulations in the VTA.Molecular brain · 2019Article
- Supervised and Unsupervised End-to-End Deep Learning for Gene Ontology Classification of Neural In Situ Hybridization Images.Entropy (Basel, Switzerland) · 2019Article
- Brain transcriptome atlases: a computational perspective.Brain structure & function · 2017Review
- Comparing the Expression of Genes Related to Serotonin (5-HT) in C57BL/6J Mice and Humans Based on Data Available at the Allen Mouse Brain Atlas and Allen Human Brain Atlas.Neurology research international · 2017Article
- Parvalbumin-Neurons of the Ventrolateral Hypothalamic Parvafox Nucleus Receive a Glycinergic Input: A Gene-Microarray Study.Frontiers in molecular neuroscience · 2017Article
- Analysis of spatial-temporal gene expression patterns reveals dynamics and regionalization in developing mouse brain.Scientific reports · 2016Article
- FuncISH: learning a functional representation of neural ISH images.Bioinformatics (Oxford, England) · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
motivationGene expression patterns can be useful in understanding the structural organization of the brain and the regulatory logic that governs its myriad cell types. A particularly rich source of spatial expression data is the Allen Brain Atlas (ABA), a comprehensive genome-wide in situ hybridization study of the adult mouse brain. Here, we present an open-source program, ALLENMINER, that searches the ABA for genes that are expressed, enriched, patterned or graded in a user-specified region of interest.
resultsRegionally enriched genes identified by ALLENMINER accurately reflect the in situ data (95-99% concordance with manual curation) and compare with regional microarray studies as expected from previous comparisons (61-80% concordance). We demonstrate the utility of ALLENMINER by identifying genes that exhibit patterned expression in the caudoputamen and neocortex. We discuss general characteristics of gene expression in the mouse brain and the potential application of ALLENMINER to design strategies for specific genetic access to brain regions and cell types. AVAILABILITY: ALLENMINER is freely available on the Internet at http://research.janelia.org/davis/allenminer.
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.