This tutorial shows how to obtain coordinates of genes, then input those coordinates into the UCSC Genome Browser for display. The regions do not have to be continuous in the genome.

This tutorial demonstrates the Multi-Region Exon-Only Display mode of the UCSC Genome Browser.

This tutorial demonstrates viewing alternate haplotypes with the UCSC Genome Browser.

The Genome Browser in the Cloud (GBiC) program is a convenient tool that automates the setup of a UCSC Genome Browser mirror​ on a cloud instance or a dedicated physical server.

This tutorial gives a demonstration of species/genome assembly selection page (Gateway) on the UCSC Genome Browser.

This tutorial demonstrates how to get the coordinates and sequences of exons using the UCSC Genome Browser.

This tutorial will demonstrate how to locate amino acid numbers for coding genes using the UCSC Genome Browser.

This tutorial will demonstrate how to find the tables in the UCSC database that are associated with the data tracks in the Genome Browser graphical viewer.

This tutorial shows how to navigate between exons of a gene using the UCSC Genome Browser.

This demonstration walks through how to import your data into MATLAB.

This lesson provides instruction regarding the various factors one must consider when preprocessing data, preparing it for statistical exploration and analyses. 

This tutorial outlines, step by step, how to perform analysis by group and how to do change-point detection.

This tutorial walks through several common methods for visualizing your data in different ways depending on your data type.

This tutorial illustrates several ways to approach predictive modeling and machine learning with MATLAB.

This brief tutorial goes over how you can easily work with big data as you would with any size of data.

In this tutorial, you will learn how to deploy your models outside of your local MATLAB environment, enabling wider sharing and collaboration.

This video gives a short introduction to the EBRAINS data sharing platform, why it was developed, and how it contributes to open data sharing.

This video introduces the key principles for data organization and explains how you could make your data FAIR for data sharing on EBRAINS.

An introduction to data management, manipulation, visualization, and analysis for neuroscience. Students will learn scientific programming in Python, and use this to work with example data from areas such as cognitive-behavioral research, single-cell recording, EEG, and structural and functional MRI. Basic signal processing techniques including filtering are covered. The course includes a Jupyter Notebook and video tutorials.

This lesson provides a hands-on tutorial for generating simulated brain data within the EBRAINS ecosystem.