Computing for Cancer Informatics (Coursera)

Computing for Cancer Informatics (Coursera)

One of the key cancer informatics challenges 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 to understand the basics of computing and to familiarize them with various computing options to ultimately help guide their decisions on the topic.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

This course aims to provide research leaders with awareness and guidance about:

  • Basic computing terminology
  • Concepts about how computers and computing systems work
  • Differences between shared computing resources
  • Appropriate etiquette for shared computing resources
  • Computing resources designed for cancer research
  • Considerations for computing resource decisions

What You Will Learn

  • Basics about how computers and shared computing resources work.
  • Understanding of the benefits and drawbacks of currently available computing resource options, especially for cancer research.
  • Understanding of important considerations when making computing decisions.

Syllabus

WEEK 1
Welcome
In this module we will introduce you to how the material will be presented and the goals for the course.
Basic Building Block of Computers
In this module we will start by describing some basics about how computers work. We feel that familiarity with this information will be helpful for you when you need to make computing decisions for your work.

WEEK 2
Binary data to computations
In this module we will talk about how computers store and process data. This will be helpful for understanding computing and storage requirements for your work.

WEEK 3
Computing Resources
In this module we will describe some basics about file sizes and computing capacity. We will specifically focus on common types of files used in cancer research. We will also introduce some general concepts for shared computing resource, which can be a great option if you wish to do work that might be too intensive for your personal computer.
Shared Computing Etiquette
In this module we will describe some common good practices for using traditional shared computing resources like clusters. These guidelines will help ensure that you don't use shared resources in a way that might bother others, so that you can continue to have access to such shared resources.

WEEK 4
Research Platforms
In this module we will take you through a tour of some computing resource platforms designed for researchers, including some that may be especially useful to cancer researchers.
Data Management Decisions
In this final module we will provide guidance about how to decide what computing resources would be most beneficial for your work.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Algorithmic Thinking (Part 1) (Coursera) Coursera
Rice University

Algorithmic Thinking (Part 1) (Coursera)

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems.

Aug 10th 2026
4 Weeks
Bacterial Bioinformatics (Coursera) Coursera
University of Virginia

Bacterial Bioinformatics (Coursera)

This course provides demonstrations and exercises for performing common genomics-based analysis tasks of bacterial sequence data. It uses PATRIC, the PathoSystems Resource Integration Center, as the platform for analysis. PATRIC is the NIH/NIAID-funded bacterial Bioinformatics Resource Center, providing comprehensive bacterial genomic data with integrated analysis tools and visualizations.

Aug 17th 2026
5-12 Weeks
Bioinformatic Methods II (Coursera) Coursera
University of Toronto

Bioinformatic Methods II (Coursera)

Large-scale biology projects such as the sequencing of the human genome and gene expression surveys using RNA-seq, microarrays and other technologies have created a wealth of data for biologists. However, the challenge facing scientists is analyzing and even accessing these data to extract useful information pertaining to the system being studied. This course focuses on employing existing bioinformatic resources – mainly web-based programs and databases – to access the wealth of data to answer questions relevant to the average biologist, and is highly hands-on.

Aug 3rd 2026
5-12 Weeks
FPGA computing systems: Background knowledge and introductory materials (Coursera) Coursera
Politecnico di Milano

FPGA computing systems: Background knowledge and introductory materials (Coursera)

This course is for anyone passionate in learning how a hardware component can be adapted at runtime to better respond to users/environment needs. This adaptation can be provided by the designers, or it can be an embedded characteristic of the system itself. These runtime adaptable systems will be implemented by using FPGA technologies.

Aug 10th 2026
4 Weeks
Documentation and Usability for Cancer Informatics (Coursera) Coursera
Johns Hopkins University

Documentation and Usability for Cancer Informatics (Coursera)

Cancer datasets are plentiful, complicated, and hold information that may be critical for the next research advancements. In order to use these data to their full potential, researchers are dependent on the specialized data tools that are continually being published and developed. Bioinformatics tools can often be unfriendly to their users, who often have little to no background in programming (Bolchini et al. 2008). The usability and quality of the documentation of a tool can be a major factor in how efficiently a researcher is able to obtain useful findings for the next steps of their research.

Aug 10th 2026
4 Weeks
AWS Cloud Practitioner Essentials (Coursera) Coursera
AWS

AWS Cloud Practitioner Essentials (Coursera)

Welcome to AWS Cloud Practitioner Essentials. If you’re new to the cloud, whether you’re in a technical or non-technical role such as finance, legal, sales, marketing, this course will provide you with an understand of fundamental AWS Cloud concepts to help you gain confidence to contribute to your organization’s cloud initiatives. This course is also the starting point to prepare for your AWS Certified Cloud Practitioner certification whenever it’s convenient for you.

Aug 10th 2026
5-12 Weeks
Comparing Genes, Proteins, and Genomes (Bioinformatics III) (Coursera) Coursera
University of California, San Diego

Comparing Genes, Proteins, and Genomes (Bioinformatics III) (Coursera)

Once we have sequenced genomes in the previous course, we would like to compare them to determine how species have evolved and what makes them different. In the first half of the course, we will compare two short biological sequences, such as genes (i.e., short sequences of DNA) or proteins. We will encounter a powerful algorithmic tool called dynamic programming that will help us determine the number of mutations that have separated the two genes/proteins.

Aug 17th 2026
5-12 Weeks
Advanced Reproducibility in Cancer Informatics (Coursera) Coursera
Johns Hopkins University

Advanced Reproducibility in Cancer Informatics (Coursera)

This course introduces tools that help enhance reproducibility and replicability in the context of cancer informatics. It uses hands-on exercises to demonstrate in practical terms how to get acquainted with these tools but is by no means meant to be a comprehensive dive into these tools. The course introduces tools and their concepts such as git and GitHub, code review, Docker, and GitHub actions.

Aug 17th 2026
5-12 Weeks