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.

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.

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.

Tutorial on collaborating with Git and GitHub. This tutorial was part of the 2019 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

This lecture and tutorial focuses on measuring human functional brain networks. The lecture and tutorial were part of the 2019 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Lecture on functional brain parcellations and a set of tutorials on bootstrap agregation of stable clusters (BASC) for fMRI brain parcellation which were part of the 2019 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Neuronify is an educational tool meant to create intuition for how neurons and neural networks behave. You can use it to combine neurons with different connections, just like the ones we have in our brain, and explore how changes on single cells lead to behavioral changes in important networks. Neuronify is based on an integrate-and-fire model of neurons. This is one of the simplest models of neurons that exist. It focuses on the spike timing of a neuron and ignores the details of the action potential dynamics. These neurons are modeled as simple RC circuits. When the membrane potential is above a certain threshold, a spike is generated and the voltage is reset to its resting potential. This spike then signals other neurons through its synapses.

Neuronify aims to provide a low entry point to simulation-based neuroscience.

This session will include presentations of infrastructure that embrace the FAIR principles developed by members of the INCF Community. This lecture provides an overview and demo of the Canadian Open Neuroscience Platform (CONP).

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 organisation and explains how you could make your data FAIR for data sharing on EBRAINS.

This video explains what metadata is, why it is important, and how you can organise your metadata to increase the FAIRness of your data on EBRAINS.

This video introduces the importance of writing a Data Descriptor to accompany your dataset on EBRAINS. It gives concrete examples on what information to include and highlights how this makes your data more FAIR.

This video demonstrates how to find, access, and download data on EBRAINS.