Grant Number:	5R25GM123516-02 Interpret this number
Primary Investigator:	Churchill, Gary
Organization:	Jackson Laboratory
Project Title:	Curriculum Development and Training for Systems Genetics
Fiscal Year:	2017

PROJECT SUMMARY/ABSTRACT Biomedical research has been recast into a data intensive science by digital technologies that produce enormous quantities of data. New capabilities in biomedical research have emerged as a result of this transformation; however, training to realize these new capabilities has lagged. New research capabilities require a workforce with sophisticated training in methods for Big Data analysis. We propose to provide the advanced training in statistical inference, modeling, and high-throughput sequence analysis that biomedical researchers need to reach new breakthroughs in medicine and health. Our goal is to produce biomedical researchers skilled in advanced statistical methods and to nurture interdisciplinary collaboration. The Churchill group at The Jackson Laboratory will leverage its expertise in statistical analysis of large-scale data to create a cutting-edge Curriculum and Training for Systems Genetics. Our specific aims include 1) develop a modular curriculum for advanced training in genomic data analysis, 2) test and evaluate the curriculum at The Jackson Laboratory with an audience of practicing scientists, postdoctoral fellows, and graduate students, and 3) disseminate the curriculum through Software Carpentry's global instructor network. Software Carpentry teaches basic laboratory skills for scientific computing. We will train members of Software Carpentry's community of volunteer scientist-instructors to teach our curriculum. Trained instructors will then broadcast advanced instruction in statistical analysis of Big Data to researchers at numerous biomedical institutions. Data Carpentry, a sibling organization of Software Carpentry, will assist us in integrating our curriculum with its genomics workshop to create seamless domain-specific training from introductory to advanced content. The full curriculum will be available on the web under an open license for teaching and self-study.




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Authors: McClatchy S. , Bass K.M. , Gatti D.M. , Moylan A. , Churchill G. .
Source: Plos Computational Biology, 2020 07; 16(7), p. e1008007.
EPub date: 2020-07-23 00:00:00.0.
PMID: 32702019
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