Icahn School of Medicine at Mount Sinai
Big Data Science with the BD2K-LINCS Data Coordination and Integration Center

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Icahn School of Medicine at Mount Sinai

Big Data Science with the BD2K-LINCS Data Coordination and Integration Center

Avi Ma’ayan, PhD

Instructor: Avi Ma’ayan, PhD

6,213 already enrolled

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Gain insight into a topic and learn the fundamentals.
4.8

(25 reviews)

Intermediate level
Some related experience required
9 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.8

(25 reviews)

Intermediate level
Some related experience required
9 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace

Details to know

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Assessments

2 assignments

Taught in English

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There are 14 modules in this course

This module provides an overview of the concept behind the LINCS program; and tutorials on how to get started with using the LINCS L1000 dataset.

What's included

8 videos2 readings1 discussion prompt

This module includes a broad high level description of the concepts behind metadata and ontologies and how these are applied to LINCS datasets.

What's included

2 videos

In this module we explain the concept of accessing data through an application programming interface (API).

What's included

2 videos1 discussion prompt

This module describes the important concept of a Bioinformatics pipeline.

What's included

1 video1 discussion prompt

This module describes a project that integrates many resources that contain knowledge about genes and proteins. The project is called the Harmonizome, and it is implemented as a web-server application available at: http://amp.pharm.mssm.edu/Harmonizome/

What's included

4 videos1 discussion prompt

This module describes the mathematical concepts behind data normalization.

What's included

2 videos1 discussion prompt

This module describes the mathematical concepts behind data clustering, or in other words unsupervised learning - the identification of patterns within data without considering the labels associated with the data.

What's included

3 videos1 discussion prompt

The Midterm Exam consists of 45 multiple choice questions which covers modules 1-7. Some of the questions may require you to perform some analysis with the methods you learned throughout the course on new datasets.

What's included

1 assignment

This module introduces the important concept of performing gene set enrichment analyses. Enrichment analysis is the process of querying gene sets from genomics and proteomics studies against annotated gene sets collected from prior biological knowledge.

What's included

3 videos

This module describes the mathematical concepts of supervised machine learning, the process of making predictions from examples that associate observations/features/attribute with one or more properties that we wish to learn/predict.

What's included

3 videos1 discussion prompt

This module discusses how Bioinformatics pipelines can be compared and evaluated.

What's included

2 videos1 discussion prompt

This module provides programming examples on how to get started with creating interactive web-based data visualization elements/figures.

What's included

4 videos1 discussion prompt

This final module describes opportunities to work on LINCS related projects that go beyond the course.

What's included

2 videos1 reading

The Final Exam consists of 60 multiple choice questions which covers all of the modules of the course. Some of the questions may require you to perform some analysis with the methods you learned throughout the course on new datasets.

What's included

1 assignment

Instructor

Instructor ratings
4.8 (5 ratings)
Avi Ma’ayan, PhD
Icahn School of Medicine at Mount Sinai
2 Courses26,317 learners

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