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.

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

A brief overview of the Python programming language, with an emphasis on tools relevant to data scientists. This lecture was part of the 2018 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

This tutorial was part of the 2018 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

This tutorial was part of the 2018 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Agah Karakuzu takes a spaghetti script written in MATLAB and turns it into understandable and reusable code living happily in a powerful GitHub repository.

Basic knowledge and comfort with Command Line Interfaces (CLI) is highly beneficial for learning how to use countless neuroscience tools and acquiring programming skills.  Furthermore, CLIs are better disposed to reproducibility, automation, concatenation in pipelines, execution on multiple platforms, and remote access.

Ross Markello takes you through this general introduction to the essentials of navigating through a Bash terminal environment.  The lesson is based on the Software Carpentries "Introduction to the Shell" and was given in the context of the BrainHack School 2020.

Ross Markello provides an overview of Python applications to data analysis, demonstrating why it has become ubiquitous in data science and neuroscience.

The lesson was given in the context of the BrainHack School 2020.

How genetics can contribute to our understanding of psychiatric phenotypes.

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.

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.