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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
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Tutorial describing the basic search and navigation features of the Allen Mouse Brain Atlas

Difficulty level: Beginner
Duration: 6:40
Speaker: : Unknown
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Tutorial describing the basic search and navigation features of the Allen Developing Mouse Brain Atlas

Difficulty level: Beginner
Duration: 6:35
Speaker: : Unknown
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Tutorial describing the basic features of the Brain Explorer® 3-D viewer for the mouse brain

Difficulty level: Beginner
Duration: 6:41
Speaker: : Unknown
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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.

Difficulty level: Beginner
Duration: 6:31
Speaker: : Unknown
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The chair of the workshop is giving an introduction and a motivating argument.

Difficulty level: Beginner
Duration: 5:36
Speaker: : Maryann Martone
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This lecture highlights the importance of correct annotation and assignment of location, and updated atlas resources to avoid errors in navigation and data interpretation.

Difficulty level: Intermediate
Duration: 22:04
Speaker: : Trygve Leergard
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We are at the exciting technological stage where it has become feasible to represent the anatomy of an entire human brain at the cellular level. In this presentation, the speaker explains that neuroanatomy in the XXI Century has become an effort towards the virtualization and standardization of brain tissue.

Difficulty level: Intermediate
Duration: 25:27
Speaker: : Jacopo Annese
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This lecture covers essential features of digital brain models for neuroinformatics.

Difficulty level: Intermediate
Duration: 22:26
Speaker: : Douglas Bowden
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This presentation covers the neuroinformatics tools and techniques used and their relationship to neuroanatomy for the Allen atlases of the mouse, developing mouse, and mouse connectional atlas.

Difficulty level: Intermediate
Duration: 23:41
Speaker: : Mike Hawrylycz
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This lecture covers modeling the neuron in silicon, modeling vision and audition and sensory fusion using a deep network. 

Difficulty level: Beginner
Duration: 1:32:17
Speaker: : Shih-Chii Liu
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Presentation of a simulation software for spatial model neurons and their networks designed primarily for GPUs.

Difficulty level: Beginner
Duration: 21:15
Speaker: : Tadashi Yamazaki
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Presentation of past and present neurocomputing approaches and hybrid analog/digital circuits that directly emulate the properties of neurons and synapses.

Difficulty level: Beginner
Duration: 41:57
Speaker: : Giacomo Indiveri
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Presentation of the Brian neural simulator, where models are defined directly by their mathematical equations and code is automatically generated for each specific target.

Difficulty level: Beginner
Duration: 20:39
Speaker: : Giacomo Indiveri
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The lecture covers a brief introduction to neuromorphic engineering, some of the neuromorphic networks that the speaker has developed, and their potential applications, particularly in machine learning.

Difficulty level: Intermediate
Duration: 19:57
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Introduction to the Mathematics chapter of Datalabcc's "Foundations in Data Science" series.

Difficulty level: Beginner
Duration: 2:53
Speaker: : Barton Poulson
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Primer on elementary algebra

Difficulty level: Beginner
Duration: 3:03
Speaker: : Barton Poulson
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Primer on linear algebra

Difficulty level: Beginner
Duration: 5:38
Speaker: : Barton Poulson
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Primer on systems of linear equations

Difficulty level: Beginner
Duration: 5:24
Speaker: : Barton Poulson
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Primer on calculus

Difficulty level: Beginner
Duration: 4:17
Speaker: : Barton Poulson