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Chapter 1 Introduction

Computing for Cancer Research. Written by: Carrie Wright. Contributed and Edited by: Sarah Wheelan and Jeff Leek

1.1 Motivation

One of the key challenges in cancer informatics is dealing with and managing the explosion of large data from multiple sources that are often too large to work with on typical personal computers. This course is designed to help researchers and investigators understand the basics of computing and to familiarize them with various computing options, ultimately helping their research decisions.

1.2 Target Audience

This course is intended for researchers, including postdocs and students, with limited to intermediate experience with informatics research. The conceptual material will also be useful for those in management roles who are collecting data and using informatics pipelines.

For individuals whom: Have no formal training in informatics. Are relatively new to informatics. Want to learn the basics of computers and shared computing resources. Want guidance for choosing computing options

1.3 Topics covered:

Concepts discussed in the Computing for Cancer Informatics course: How computer hardware and software work. Computing resources designed for research Data sizes and computational capacity. Guidance about computing resource decisions. How shared computing resources work. Etiquette for shared computing resources.

1.4 Curriculum

The course will cover key underlying principles and concepts in computing. We will go over concrete discussions of the differences between cloud and local computing. The course will also highlight a number of computing options and describe etiquette basics for using shared resources.

Overall Course Learning Objectives. This course will demonstrate how to: 1.Recognize various data management systems especially for cancer research related data, 2.Compare and make informed decisions about computation platforms (including economic considerations),3.Implement best practices for data security and privacy, 4. Share data safely and securely in a variety of contexts,5.Handle IRB and data access requests,6.Apply ethical consideration in data management workflows