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Genomic Data Science and Clustering (Bioinformatics V)

Bioinformatics,

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.

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Rating 4.0★ based on 16 ratings
Length 4 weeks
Starts Jul 3 (43 weeks ago)
Cost $79
From University of California San Diego via Coursera
Instructors Pavel Pevzner, Phillip E. C. Compeau, Phillip Compeau
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Science
Tags Computer Science Life Sciences Algorithms Bioinformatics Health Informatics

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What people are saying

peer reviewed final challenge

What I liked best was that this course didn't have a peer reviewed final challenge, so I didn't have to wait months until my work was graded :) This course is too Short and not up to date with deep learning In depth and comprehensive coverage of the topics in genetic data analysis.

class without some pre-knowledge

Just jump into this class without some pre-knowledge will be quite difficult.

deeply into developing hard

This course goes deeply into developing hard and soft k mean clustering algorithms.

soft k mean clustering

connection with genomic data

The first two week was very good, but for week 3 I don't see the content has any connection with Genomic Data Science.

genetic data analysis

wait months until

just jump into

material are poor

very excellent course Material are poor... missing information about content asked in the quiz... the forum is not moderated... and Quiz 2 have a problem with inputs!

absolutely fantastic

Absolutely fantastic course.

highly recommend

Highly recommend the course and the specializations to all learners who are serious about learning algorithms.

truly awesome

good course Truly awesome.

Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile.

AD, Data Science $47k

Associate Data Science Supervisor $55k

Science writer / data analyst $63k

Genomic Data Science Programmer $75k

Volunteer Director of Data Science $78k

Expert Data Science Supervisor $79k

Supervisor 1 Data Science Supervisor $91k

Guest Director of Data Science $101k

Data Science Architect $105k

Head of Data Science $131k

Assistant Director 1 of Data Science $133k

Owner Director of Data Science $149k

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Rating 4.0★ based on 16 ratings
Length 4 weeks
Starts Jul 3 (43 weeks ago)
Cost $79
From University of California San Diego via Coursera
Instructors Pavel Pevzner, Phillip E. C. Compeau, Phillip Compeau
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Science
Tags Computer Science Life Sciences Algorithms Bioinformatics Health Informatics

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