This tutorial talks about how to upload and version your data in OpenNeuro.org
Tutorial describing the basic search and navigation features of the Allen Mouse Brain Atlas
Tutorial describing the basic search and navigation features of the Allen Developing Mouse Brain Atlas
This tutorial demonstrates how to use the differential search feature of the Allen Mouse Brain Atlas to find gene markers for different regions of the brain and to visualize this gene expression in three-dimensional space. Differential search is also available for the Allen Developing Mouse Brain Atlas and the Allen Human Brain Atlas.
The practical usage of The Virtual brain in its graphical user interface and via python scripts is introduced. In the graphical user interface, you are guided through its data repository, simulator, phase plane exploration tool, connectivity editor, stimulus generator and the provided analyses. The implemented iPython notebooks of TVB are presented, and since they are public, can be used for further exploration of The Virtual brain.
Manipulate the default connectome provided with TVB to see how structural lesions effect brain dynamics. In this hands-on session you will insert lesions into the connectome within the TVB graphical user interface. Afterwards the modified connectome will be used for simulations and the resulting activity will be analysed using functional connectivity.
Research Resource Identifiers (RRIDs) are ID numbers assigned to help researchers cite key resources (antibodies, model organisms and software projects) in the biomedical literature to improve transparency of research methods.
GeneWeaver is a web application for the integrated cross-species analysis of functional genomics data to find convergent evidence from heterogeneous sources. The application consists of a large database of gene sets curated from multiple public data resources and curated submissions, along with a suite of analysis tools designed to allow flexible, customized workflows through web-based interactive analysis or scripted API driven analysis. Gene sets come from multiple widely studied species and include ontology annotations, brain gene expression atlases, systems genetic study results, gene regulatory information, pathway databases, drug interaction databases and many other sources. Users can retrieve, store, analyze and share gene sets through a graded access system. Analysis tools are based on combinatorics and statistical methods for comparing, contrasting and classifying gene sets based on their members.
This tutorial shows how to use the UCSC genome browser to find a list of genes in a given genomic region.
This tutorial shows how to find all the single nucleotide polymorphisms upstream from genes using the UCSC Genome Browser.
This tutorial demonstrates how to find all the single nucleotide polymorphisms in a gene using the UCSC Genome Browser.
The Saved Sessions feature of the Browser has been around for quite some time, but many of our users have not made full use of it. It offers a great way to keep track of your thinking on a particular topic.
This tutorial demonstrates the visibility controls on the Genome Browser, showing the affect on BED tracks, wiggle tracks and Conservation tracks. It also discusses supertracks and composite tracks.
This tutorial describes the isPCR tool and demonstrates how to use it for predicting the size and location of PCR products and visualizing the genomic location on the genome. The tool operates on DNA templates for all organisms and DNA or RNA on human and mouse. It also demonstrates how to use the Browser to obtain DNA sequences from the genome.
This tutorial describes the dbSNP resources in the UCSC Genome Browser, including display conventions and the subdivision of the data into several useful subset tracks, especially the Common SNPs. There is also a discussion about changes to the genome assemblies from one version to another, and of two ways to navigate between different assemblies of the human genome in the Browser.
This tutorial demonstrates the Data Integrator, a tool that allows combination and intersection of data from up to five primary tables. In the example, data are extracted showing SNPs, genes and phenotypes from a genomic region.
This tutorial shows how to obtain coordinates of genes, then input those coordinates into the Genome Browser for display. The regions do not have to be continuous in the genome.