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The Mouse Phenome Database (MPD) provides access to primary experimental trait data, genotypic variation, protocols and analysis tools for mouse genetic studies. Data are contributed by investigators worldwide and represent a broad scope of phenotyping endpoints and disease-related traits in naïve mice and those exposed to drugs, environmental agents or other treatments. MPD ensures rigorous curation of phenotype data and supporting documentation using relevant ontologies and controlled vocabularies. As a repository of curated and integrated data, MPD provides a means to access/re-use baseline data, as well as allows users to identify sensitized backgrounds for making new mouse models with genome editing technologies, analyze trait co-inheritance, benchmark assays in their own laboratories, and many other research applications. MPD’s primary source of funding is NIDA. For this reason, a majority of MPD data is neuro- and behavior-related.

Difficulty level: Beginner
Duration: 55:36
Speaker: : Elissa Chesler

This lecture provides an introduction to the course "Cognitive Science & Psychology: Mind, Brain, and Behavior".

Difficulty level: Beginner
Duration: 1:06:49

This lesson covers the history of neuroscience and machine learning, and the story of how these two seemingly disparate fields are increasingly merging. 

Difficulty level: Beginner
Duration: 12:25
Speaker: : Dan Goodman

This lecture focuses on the structured validation process within computational neuroscience, including the tools, services, and methods involved in simulation and analysis.

Difficulty level: Beginner
Duration: 14:19
Speaker: : Michael Denker

This module explains how neurons come together to create the networks that give rise to our thoughts. The totality of our neurons and their connection is called our connectome. Learn how this connectome changes as we learn, and computes information.

Difficulty level: Beginner
Duration: 7:13
Speaker: : Harrison Canning

In this lesson, you will learn about data management within the Open Data Commons (ODC) framework, and in particular, how Spinal Cord Injury (SCI) data is stored, shared, and published. You will also hear about Frictionless Data, an open-source toolkit aimed at simplifying the data experience. 

Difficulty level: Beginner
Duration: 19:10

This lesson introduces several open science tools like Docker and Apptainer which can be used to develop portable and reproducible software environments. 

Difficulty level: Beginner
Duration: 17:22
Speaker: : Joanes Grandjean

This talk covers the differences between applying HED annotation to fMRI datasets versus other neuroimaging practices, and also introduces an analysis pipeline using HED tags. 

Difficulty level: Beginner
Duration: 22:52
Speaker: : Monique Denissen

This lesson provides a brief visual walkthrough on the necessary steps when copying data from one brainlife project to another. 

Difficulty level: Beginner
Duration: 1:07
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This lesson visually documents the process of uploading data to brainlife via the command line interface (CLI). 

Difficulty level: Beginner
Duration: 1:28
Speaker: :

This video shows how to use the brainlife.io interface to edit the participants' info file. This file is the ParticipantInfo.json file of the Brain Imaging Data Structure (BIDS).

Difficulty level: Beginner
Duration: 0:34
Speaker: :

This video will document the process of running an app on brainlife, from data staging to archiving of the final data outputs.

Difficulty level: Beginner
Duration: 3:43
Speaker: :

This video demonstrates each required step for preprocessing T1w anatomical data in brainlife.io.

Difficulty level: Beginner
Duration: 3:28
Speaker: :

This short video shows how data in a brainlife.io publication can be opened from a DOI inside a published article. The video provides an example of how the DOI deposited on the journal can be opened with a web browser to redirect to the associated data publication on brainlife.io.

Difficulty level: Beginner
Duration: 2:18
Speaker: :

This lecture contains an overview of electrophysiology data reuse within the EBRAINS ecosystem.

Difficulty level: Beginner
Duration: 15:57
Speaker: : Andrew Davison

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

Difficulty level: Beginner
Duration: 17:23
Speaker: : Ulrike Schlegel
Course:

Maximize Your Research With Cloud Workspaces is a talk aimed at researchers who are looking for innovative ways to set up and execute their life science data analyses in a collaborative, extensible, open-source cloud environment. This panel discussion is brought to you by MetaCell and scientists from leading universities who share their experiences of advanced analysis and collaborative learning through the Cloud.

 

Difficulty level: Beginner
Duration: 55:43

This brief video provides an introduction to the third session of INCF's Neuroinformatics Assembly 2023, focusing on how to streamling cross-platform data integration in a neuroscientific context. 

Difficulty level: Beginner
Duration: 5:55
Speaker: : Bing-Xing Huo

This talk describes the challenges to sustained operability and success of consortia, why many of these groups flounder after just a few years, and what steps can be taken to mitigate such outcomes. 

Difficulty level: Beginner
Duration: 18:29
Speaker: : Maryann Martone

This talk discusses the BRAIN Initiative Cell Atlas Network (BICAN), taking a look specifically at how this network approaches the design, development, and maintenance of specimen and sequencing library portals. 

Difficulty level: Beginner
Duration: 15:08
Speaker: : GQ Zhang