ArticlePLoS computational biology2012
Localizing genes to cerebellar layers by classifying ISH images.
Article in PLoS computational biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 36 citations in OpenAlex.
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- SMASH: Scalable Method for Analyzing Spatial Heterogeneity of genes in spatial transcriptomics data.PLoS genetics · 2023Article
- Spatial transcriptomic analysis of Sonic hedgehog medulloblastoma identifies that the loss of heterogeneity and promotion of differentiation underlies the response to CDK4/6 inhibition.Genome medicine · 2023Article
- Spatially aware dimension reduction for spatial transcriptomics.Nature communications · 2022Article
- Scalable and model-free detection of spatial patterns and colocalization.Genome research · 2022Article
- The role of histone modifications: from neurodevelopment to neurodiseases.Signal transduction and targeted therapy · 2022Review
- Artificially Induced Pluripotent Stem Cell-Derived Whole-Brain Organoid for Modelling the Pathophysiology of Metachromatic Leukodystrophy and Drug Repurposing.Biomedicines · 2021Article
- NEUBOrg: Artificially Induced Pluripotent Stem Cell-Derived Brain Organoid to Model and Study Genetics of Alzheimer's Disease Progression.Frontiers in aging neuroscience · 2021Article
- Erbb4 Is Required for Cerebellar Developmentand Malignant Phenotype of Medulloblastoma.Cancers · 2020Article
- Application of Computational Biology to Decode Brain Transcriptomes.Genomics, proteomics & bioinformatics · 2019Review
- Neuronal Activities in the Mouse Visual Cortex Predict Patterns of Sensory Stimuli.Neuroinformatics · 2018Article
- Cell-type-specific metabolic labeling of nascent proteomes in vivo.Nature biotechnology · 2017Article
- Brain transcriptome atlases: a computational perspective.Brain structure & function · 2017Review
- Defining Trends in Global Gene Expression in Arabian Horses with Cerebellar Abiotrophy.Cerebellum (London, England) · 2017Article
- On Expression Patterns and Developmental Origin of Human Brain Regions.PLoS computational biology · 2016Article
- Deep convolutional neural networks for annotating gene expression patterns in the mouse brain.BMC bioinformatics · 2015Article
- Laminar and dorsoventral molecular organization of the medial entorhinal cortex revealed by large-scale anatomical analysis of gene expression.PLoS computational biology · 2015Article
- Automated identification of cell-type-specific genes in the mouse brain by image computing of expression patterns.BMC bioinformatics · 2014Article
- FuncISH: learning a functional representation of neural ISH images.Bioinformatics (Oxford, England) · 2013Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gene expression controls how the brain develops and functions. Understanding control processes in the brain is particularly hard since they involve numerous types of neurons and glia, and very little is known about which genes are expressed in which cells and brain layers. Here we describe an approach to detect genes whose expression is primarily localized to a specific brain layer and apply it to the mouse cerebellum. We learn typical spatial patterns of expression from a few markers that are known to be localized to specific layers, and use these patterns to predict localization for new genes. We analyze images of in-situ hybridization (ISH) experiments, which we represent using histograms of local binary patterns (LBP) and train image classifiers and gene classifiers for four layers of the cerebellum: the Purkinje, granular, molecular and white matter layer. On held-out data, the layer classifiers achieve accuracy above 94% (AUC) by representing each image at multiple scales and by combining multiple image scores into a single gene-level decision. When applied to the full mouse genome, the classifiers predict specific layer localization for hundreds of new genes in the Purkinje and granular layers. Many genes localized to the Purkinje layer are likely to be expressed in astrocytes, and many others are involved in lipid metabolism, possibly due to the unusual size of Purkinje cells.
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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.