How do we infer which genes orchestrate various processes in the cell? How did humans migrate out of Africa and spread around the world? In this class, we will see that these two seemingly different questions can be addressed using similar algorithmic and machine learning techniques arising from the general problem of dividing data points into distinct clusters.
In the first half of the course, we will introduce algorithms for clustering a group of objects into a collection of clusters based on their similarity, a classic problem in data science, and see how these algorithms can be applied to gene expression data.
In the second half of the course, we will introduce another classic tool in data science called principal components analysis that can be used to preprocess multidimensional data before clustering in an effort to greatly reduce the number dimensions without losing much of the "signal" in the data.
Finally, you will learn how to apply popular bioinformatics software tools to solve a real problem in clustering.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Bioinformatik
Genomic Data Science and Clustering (Bioinformatics V)
von
Lehrplan - Was Sie in diesem Kurs lernen werden
Woche
15 Stunden zum Abschließen
Week 1: Introduction to Clustering Algorithms
<p>Welcome to class!</p><p>At the beginning of the class, we will see how algorithms for <strong>clustering </strong>a set of data points will help us determine how yeast became such good wine-makers. At the bottom of this email is the Bioinformatics Cartoon for this chapter, courtesy of <a href="http://bearandfox.com" target="_blank" title="Link: http://bearandfox.com">Randall Christopher</a> and serving as a chapter header in the Specialization's bestselling <a href="http://bioinformaticsalgorithms.com" target="_blank">print companion</a>. How did the monkey lose a wine-drinking contest to a tiny mammal? Why have Pavel and Phillip become cavemen? And will flipping a coin help them escape their eternal boredom until they can return to the present? Start learning to find out!</p><p><img width="550" alt="" src="http://bioinformaticsalgorithms.com/images/cover/clustering_cropped.jpg" title="Image: http://bioinformaticsalgorithms.com/images/cover/clustering_cropped.jpg"></p>
5 Videos (Gesamt 33 min), 2 Lektüren, 3 Quiz
5 Videos
Which Yeast Genes are Responsible for Wine Making? 6m
Gene Expression Matrices 6m
Clustering as an Optimization Problem 10m
The Lloyd Algorithm for k-Means Clustering 5m
2 Lektüren
Course Details10m
Week 1 FAQs (Optional)
1 praktische Übung
Week 1 Quiz20m
Woche
24 Stunden zum Abschließen
Week 2: Advanced Clustering Techniques
<p>Welcome to week 2 of class!</p>
<p>This week, we will see how we can move from a "hard" assignment of points to clusters toward a "soft" assignment that allows the boundaries of the clusters to blend. We will also see how to adapt the Lloyd algorithm that we encountered in the first week in order to produce an algorithm for soft clustering. We will also see another clustering algorithm called "hierarchical clustering" that groups objects into larger and larger clusters.</p>
5 Videos (Gesamt 35 min), 1 Lektüre, 3 Quiz
5 Videos
From Coin Flipping to k-Means Clustering 4m
Expectation Maximization 7m
Soft k-Means Clustering 3m
Hierarchical Clustering 7m
1 Lektüre
Week 2 FAQs (Optional)
1 praktische Übung
Week 2 Quiz15m
Woche
31 Stunde zum Abschließen
Week 3: Introductory Algorithms in Population Genetics
2 Lektüren, 1 Quiz
2 Lektüren
Statement on This Week's Material10m
How Have Humans Populated the Earth?10m
1 praktische Übung
Week 3 Quiz10m
33%
ziehen Sie für Ihren Beruf greifbaren Nutzen aus diesem Kurs
Top-Bewertungen
A nice course to learn clustering algorithm in bioinformatics, it will be better if you take the previous class. Just jump into this class without some pre-knowledge will be quite difficult.
the part about EM is the best I know, and first time I understand the EM algorithm.
Dozenten
Pavel Pevzner
ProfessorDepartment of Computer Science and Engineering
Phillip Compeau
Visiting ResearcherDepartment of Computer Science & Engineering
Über 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.
Über die Spezialisierung Bioinformatik
Join Us in a Top 50 MOOC of All Time!
How do we sequence and compare genomes? How do we identify the genetic basis for disease? How do we construct an evolutionary Tree of Life for all species on Earth?
When you complete this Specialization, you will learn how to answer many questions in modern biology that have become inseparable from the computational approaches used to solve them. You will also obtain a toolkit of existing software resources built on these computational approaches and that are used by thousands of biologists every day in one of the fastest growing fields in science.
Although this Specialization centers on computational topics, you do not need to know how to program in order to complete it. If you are interested in programming, we feature an "Honors Track" (called "hacker track" in previous runs of the course). The Honors Track allows you to implement the bioinformatics algorithms that you will encounter along the way in dozens of automatically graded coding challenges. By completing the Honors Track, you will be a bioinformatics software professional!
Learn more about the Bioinformatics Specialization (including why we are wearing these crazy outfits) by watching our introductory video.
You can purchase the Specialization's print companion, Bioinformatics Algorithms: An Active Learning Approach, from the textbook website.
Our first course, "Finding Hidden Messages in DNA", was named a top-50 MOOC of all time by Class Central!
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