6533b85cfe1ef96bd12bd516
RESEARCH PRODUCT
Clustering of low-correlated spatial gene expression patterns in the mouse brain in the Allen Brain Atlas
Paolo RosatiDomenico TegoloCarmen Alina Lupascusubject
0301 basic medicineSettore INF/01 - InformaticaComputer scienceBrain atlasComputer Science ApplicationGenomicsComputational biologySagittal planeCorrelation03 medical and health sciences030104 developmental biology0302 clinical medicinemedicine.anatomical_structureComputer Networks and CommunicationHardware and ArchitectureCoronal planeGene expressionmedicineComputer Vision and Pattern RecognitionElectrical and Electronic EngineeringCluster analysis030217 neurology & neurosurgerydescription
In this paper, clustering techniques are applied to spatial gene expression patterns with a low genomic correlation between the sagittal and coronal projections. The data analysed here are hosted on an available public DB named ABA (Allen Brain Atlas). The results are compared to those obtained by Bohland et al. on the complementary dataset (high correlation values). We prove that, by analysing a reduced dataset,hence reducing the computational burden, we get the same accuracy in highlighting different neuroanatomical region.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2018-08-01 |