Bioinformatics Capstone: Big Data in Biology
Description
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- Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
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About this course: In this course, you will learn how to use the BaseSpace cloud platform developed by Illumina (our industry partner) to apply several standard bioinformatics software approaches to real biological data. In particular, in a series of Application Challenges will see how genome assembly can be used to track the source of a food poisoning outbreak, how RNA-Sequencing can help us analyze gene expression data on the tissue level, and compare the pros and cons of whole genome vs. whole exome sequencing for finding potentially harmful mutations in a human sample. Plus, hacker track students will have the option to build their own genome assembler and apply it to real data!
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When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan .
- Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
- Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.
About this course: In this course, you will learn how to use the BaseSpace cloud platform developed by Illumina (our industry partner) to apply several standard bioinformatics software approaches to real biological data. In particular, in a series of Application Challenges will see how genome assembly can be used to track the source of a food poisoning outbreak, how RNA-Sequencing can help us analyze gene expression data on the tissue level, and compare the pros and cons of whole genome vs. whole exome sequencing for finding potentially harmful mutations in a human sample. Plus, hacker track students will have the option to build their own genome assembler and apply it to real data!
Who is this class for: This course is aimed at technically-minded students who have completed the first six courses in the Bioinformatics Specialization.
Created by: University of California, San Diego-
Taught by: Phillip Compeau, Visiting Researcher
Department of Computer Science & Engineering -
Taught by: Pavel Pevzner, Professor
Department of Computer Science and Engineering
Chaque cours fonctionne comme un manuel interactif en proposant des vidéos préenregistrées, des quiz et des projets.
Aide de la part de vos pairsConnectez-vous à des milliers d'autres étudiants et débattez sur des idées, discutez le contenu du cours et obtenez de l'aide pour en maîtriser les concepts.
CertificatsObtenez une reconnaissance officielle pour votre travail et partagez votre réussite avec vos amis, vos collègues et vos employeurs.
University of California, San Diego UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.Syllabus
WEEK 1
Week 1: Identifying the Culprit in a Food Poisoning Outbreak
This week, we will apply genome sequencing algorithms to identify the bacterium causing a deadly food poisoning outbreak.
4 readings expand
- Lecture: Welcome to Class!
- Lecture: Special Thanks
- Lecture: Introduction
- Lecture: Databases and Tools
Graded: Application Challenge 1
WEEK 2
Week 2: Comparing Gene Expression in Tissue Samples with RNA-Seq
In this week's Application Challenge, we will learn how RNA-Sequencing can be applied to perform tissue-level gene expression analysis. In particular, which is more similar on a gene expression level: different tissues from the same organism, or analogous tissues from related species? This question was the subject of recent debate and a Twitter controversy -- read more to find out!
2 readings expand
- Lecture: Introduction
- Lecture: Databases and Tools
Graded: Application Challenge 2
WEEK 3
Week 3: Weighing the Pros and Cons of Whole Genome and Whole Exome Sequencing on a Human Sample
Comparing the differences between sequencing an entire human genome and sequencing only the exome, or the DNA that is eventually translated into protein. Can we obtain a complete picture of someone's genetic disease predispositions from only the exome, or is there information lurking in introns that can provide doctors with vital information? How do we weigh the trade-offs when considering genome and exome sequencing?
4 readings expand
- Lecture: Introduction
- Lecture: Databases and Tools
- Lecture: Walkthroughs
- Lecture: Reading: Part 3 FAQs
Graded: Application Challenge 3
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