About this Course
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Start instantly and learn at your own schedule.
Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Intermediate Level

Intermediate Level

Hours to complete

Approx. 14 hours to complete

Suggested: 4-5 hours/week...
Available languages

English

Subtitles: English
100% online

100% online

Start instantly and learn at your own schedule.
Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Intermediate Level

Intermediate Level

Hours to complete

Approx. 14 hours to complete

Suggested: 4-5 hours/week...
Available languages

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1
Hours to complete
2 hours to complete

The Library of Integrated Network-based Cellular Signatures (LINCS) Program Overview

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....
Reading
8 videos (Total 78 min), 2 readings
Video8 videos
The Connectivity Map8m
Geometrical View of the Connectivity Map Concept3m
LINCS Data and Signature Generation Centers12m
BD2K-LINCS Data Coordination and Integration Center4m
Induced Pluripotent Stem Cells (iPSCs)4m
Introduction to LINCS L1000 Data22m
L1000 Characteristic Direction Signature Search Engine (L1000CDS2) Demo13m
Reading2 readings
Syllabus10m
Grading and Logistics10m
Hours to complete
26 minutes to complete

Metadata and Ontologies

This module includes a broad high level description of the concepts behind metadata and ontologies and how these are applied to LINCS datasets....
Reading
2 videos (Total 26 min)
Video2 videos
Introduction to Metadata and Ontologies | Part 220m
Hours to complete
24 minutes to complete

Serving Data with APIs

In this module we explain the concept of accessing data through an application programming interface (API)....
Reading
2 videos (Total 19 min)
Video2 videos
Accessing and Serving Data through RESTful APIs | Part 210m
Week
2
Hours to complete
19 minutes to complete

Bioinformatics Pipelines

This module describes the important concept of a Bioinformatics pipeline....
Reading
1 video (Total 14 min)
Hours to complete
1 hour to complete

The Harmonizome

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/ ...
Reading
4 videos (Total 37 min)
Video4 videos
Processing Datasets | Part 18m
Processing Datasets | Part 29m
Processing Datasets | Part 37m
Week
3
Hours to complete
24 minutes to complete

Data Normalization

This module describes the mathematical concepts behind data normalization....
Reading
2 videos (Total 19 min)
Video2 videos
Data Normalization | Part 213m
Hours to complete
1 hour to complete

Data Clustering

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. ...
Reading
3 videos (Total 33 min)
Video3 videos
Data Clustering | Part 2 | Distance Functions 12m
Data Clustering | Part 3 | Algorithms and Evaluation15m
Hours to complete
2 hours to complete

Midterm Exam

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. ...
Reading
1 quiz
Quiz1 practice exercise
Midterm Exam30m
Week
4
Hours to complete
29 minutes to complete

Enrichment Analysis

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....
Reading
3 videos (Total 29 min)
Video3 videos
Enrichment Analysis | Part 27m
Enrichr Demo9m
Hours to complete
1 hour to complete

Machine Learning

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....
Reading
3 videos (Total 27 min)
Video3 videos
Introduction to Machine Learning | Part 2 8m
Introduction to Machine Learning | Part 39m

Instructor

Avatar

Avi Ma’ayan, PhD

Director, Mount Sinai Center for Bioinformatics
Professor, Department of Pharmacological Sciences

About Icahn School of Medicine at Mount Sinai

The Icahn School of Medicine at Mount Sinai, in New York City is a leader in medical and scientific training and education, biomedical research and patient care....

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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