Document Type

Article

Publication Date

7-23-2020

Keywords

JMG, JAXCC

JAX Source

PLoS Comput Biol 2020 Jul 23; 16(7):e1008007

PMID

32702019

DOI

https://doi.org/10.1371/journal.pcbi.1008007

Abstract

Biomedical research is becoming increasingly data driven. New technologies that generate large-scale, complex data are continually emerging and evolving. As a result, there is a concurrent need for training researchers to use and understand new computational tools. Here we describe an efficient and effective approach to developing curriculum materials that can be deployed in a research environment to meet this need.

Comments

The authors thank Karl Broman for providing a software user guide and other key materials, Tim Stearns and Georgi Kolishovski for contributing to experimental design and statistics curricula, and Dave Mellert, Asli Uyar, and Asa Thibodeau for producing new materials for image analysis and machine learning.

This is an open access article distributed under the terms of the Creative Commons Attribution License.

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