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Fundamental Methods for Genomic Analysis

Krembil Centre for Neuroinformatics

This course includes both lectures and tutorials around the management and analysis of genomic data in clinical research and care. Participants are led through the basics of genome-wide association studies (GWAS), genotypes, and polygenic risk scores, as well as novel concepts and tools for more sophisticated consideration of population stratification in GWAS.

 
INCF TrainingSpace

Session 6: Research Workflows for Collaborative Neuroscience

INCF

This course contains videos, lectures, and hands-on tutorials as part of INCF's Neuroinformatics Assembly 2023 workshop on developing robust and reproducible research workflows to foster greater collaborative efforts in neuroscience.

 
INCF TrainingSpace

Basic Mathematics for Computational Neuroscience

Alex Williams

A series of short explanations of the basic equations underlying computational neuroscience.

 
INCF TrainingSpace

UCSC Genome Browser Tutorial

University of California, Sanata Cruz (UCSC)

The UCSC Genome Browser is an online and downloadable genome browser hosted by the University of California, Santa Cruz (UCSC). It is an interactive website offering access to genome sequence data from a variety of vertebrate and invertebrate species and major model organisms, integrated with a large collection of aligned annotations.

 

Notebooks

Notebook systems are proving invaluable to skill acquisition, research documentation, publication, and reproducibility.  This series of presentations introduces the most popular platform for computational notebooks, Project Jupyter, as well as other resources like Binder and NeuroLibre. 

 
INCF TrainingSpace

INCF Assembly 2023 - Lightning Talks (Day 2)

INCF

This course consists of several lightning talks from the second day of INCF's Neuroinformatics Assembly 2023. Covering a wide range of topics, these brief talks provide snapshots of various neuroinformatic efforts such as brain-computer interface standards, dealing with multimodal animal MRI datasets, distributed data management, and several more. 

 

Foundations of Data Science

Datalabcc

Data science relies on several important aspects of mathematics. In this course, you'll learn what forms of mathematics are most useful for data science, and see some worked examples of how math can solve important data science problems.

 

Module 3: Computational Models

Mike X. Cohen

This module introduces computational neuroscience by simulating neurons according to the AdEx model. You will learn about generative modeling, dynamical systems, and F-I curves. The MATLAB code introduces live scripts and functions.

 

Introduction to Neurodata Without Borders (NWB) for MATLAB Users II

NWB Core Development Team

The Neurodata Without Borders: Neurophysiology project (NWB, https://www.nwb.org/) is an effort to standardize the description and storage of neurophysiology data and metadata. NWB enables data sharing and reuse and reduces the energy-barrier to applying data analytics both within and across labs. Several laboratories, including the Allen Institute for Brain Science, have wholeheartedly adopted NWB.

 
INCF TrainingSpace

Session 5: Infrastructure for Sensitive Data

INCF

This course consists of a three-part session from the second day of INCF's Neuroinformatics Assembly 2023. The lessons describe various on-going efforts within the fields of neuroinformatics and clinical neuroscience to adjust to the increasingly vast volumes of brain data being collected and stored.

 

High-Performance Computing (HPC)

The dimensionality and size of datasets in many fields of neuroscience research require massively parallel computing power.  Fortunately, the maturity and accessibility of virtualization technologies has made it feasible to run the same analysis environments on platforms ranging from single laptop computers up to high-performance computing networks.

 

The Virtual Brain Education Pack (TVB EduPack)

The Virtual Brain

The Virtual Brain EduPack provides didactic use cases for The Virtual Brain (TVB). Typically a use case consists of a jupyter notebook and a didactic video. EduPack use cases help the user to reproduce TVB-based publications or to get started quickly with TVB.

 

Foundations of Machine Learning in Python

NeurotechEU

Course designed for advanced learners interested in understanding the foundations of Machine Learning in Python.

General: The course consists of 15 lectures (ca. 1-2 hours each) and 15 exercise sheets (for ca. 6 hours of programming each).

Institution: High-Performance Computing and Analytics Lab, University of Bonn

 
INCF TrainingSpace

Session 8: FAIR Data: The Role of Journals

INCF

Most neuroscience journals request authors to make their data publicly available in appropriate repositories. The requirements and policies put forward by journals vary, and the services provided for different types of data also differ considerably across repositories.

 

Population-Based Data Resources & Integrative Research Methods

Krembil Centre for Neuroinformatics

As research methods and experimental technologies become ever more sophisticated, the amount of health-related data per individual which has become accessible is vast, giving rise to a corresponding need for cross-domain data integration, whole-person modelling, and improved precision medicine. This course provides lessons describing state of the art methods and repositories, as well as a tutorial on computational methods for data integration. 

 

Data Science and Neuroinformatics

INCF

Much like neuroinformatics, data science uses techniques from computational science to derive meaningful results from large complex datasets. In this session, we will explore the relationship between neuroinformatics and data science, by emphasizing a range of data science approaches and activities, ranging from the development and application of statistical methods, through the establishment of communities and platforms, and through the implementation of open-source software tools.

 

Module 2: EEG

Mike X. Cohen

In this module, you will work with human EEG data recorded during a steady-state visual evoked potential study (SSVEP, aka flicker). You will learn about spectral analysis, alpha activity, and topographical mapping. The MATLAB code introduces functions, sorting, and correlation analysis.

 

INCF Short Course: Introduction to Neuroinformatics

INCF

The emergence of data-intensive science creates a demand for neuroscience educators worldwide to deliver better neuroinformatics education and training in order to raise a generation of modern neuroscientists with FAIR capabilities, awareness of the value of standards and best practices, knowledge in dealing with big datasets, and the ability to integrate knowledge over multiple scales and methods.

 

Module 4: fMRI

Mike X. Cohen

This module covers fMRI data, including creating and interpreting flatmaps, exploring variability and average responses, and visual eccenticity. You will learn about processing BOLD signals, trial-averaging, and t-tests. The MATLAB code introduces data animations, multicolor visualizations, and linear indexing.

 

Introduction to Neurodata Without Borders (NWB) for Python Users I

NWB Core Development Team

The Neurodata Without Borders: Neurophysiology project (NWB, https://www.nwb.org/) is an effort to standardize the description and storage of neurophysiology data and metadata. NWB enables data sharing and reuse and reduces the energy-barrier to applying data analytics both within and across labs. Several laboratories, including the Allen Institute for Brain Science, have wholeheartedly adopted NWB.