The Library of Integrative Network-based Cellular Signatures (LINCS) is an NIH Common Fund program. The idea is to perturb different types of human cells with many different types of perturbations such as: drugs and other small molecules; genetic manipulations such as knockdown or overexpression of single genes; manipulation of the extracellular microenvironment conditions, for example, growing cells on different surfaces, and more. These perturbations are applied to various types of human cells including induced pluripotent stem cells from patients, differentiated into various lineages such as neurons or cardiomyocytes. Then, to better understand the molecular networks that are affected by these perturbations, changes in level of many different variables are measured including: mRNAs, proteins, and metabolites, as well as cellular phenotypic changes such as changes in cell morphology. The BD2K-LINCS Data Coordination and Integration Center (DCIC) is commissioned to organize, analyze, visualize and integrate this data with other publicly available relevant resources. In this course we briefly introduce the DCIC and the various Centers that collect data for LINCS. We then cover metadata and how metadata is linked to ontologies. We then present data processing and normalization methods to clean and harmonize LINCS data. This follow discussions about how data is served as RESTful APIs. Most importantly, the course covers computational methods including: data clustering, gene-set enrichment analysis, interactive data visualization, and supervised learning. Finally, we introduce crowdsourcing/citizen-science projects where students can work together in teams to extract expression signatures from public databases and then query such collections of signatures against LINCS data for predicting small molecules as potential therapeutics.
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Big Data Science with the BD2K-LINCS Data Coordination and Integration Center
Icahn School of Medicine at Mount SinaiAbout this Course
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Coursera Labs
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Approx. 9 hours to complete
English
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Coursera Labs
Includes hands on learning projects.
Learn more about Coursera Labs Intermediate Level
Approx. 9 hours to complete
English
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Syllabus - What you will learn from this course
2 hours to complete
The Library of Integrated Network-based Cellular Signatures (LINCS) Program Overview
2 hours to complete
8 videos (Total 78 min), 2 readings
26 minutes to complete
Metadata and Ontologies
26 minutes to complete
2 videos (Total 26 min)
29 minutes to complete
Serving Data with APIs
29 minutes to complete
2 videos (Total 19 min)
24 minutes to complete
Bioinformatics Pipelines
24 minutes to complete
1 video (Total 14 min)
1 hour to complete
The Harmonizome
1 hour to complete
4 videos (Total 37 min)
29 minutes to complete
Data Normalization
29 minutes to complete
2 videos (Total 19 min)
1 hour to complete
Data Clustering
1 hour to complete
3 videos (Total 33 min)
1 hour to complete
Midterm Exam
1 hour to complete
29 minutes to complete
Enrichment Analysis
29 minutes to complete
3 videos (Total 29 min)
1 hour to complete
Machine Learning
1 hour to complete
3 videos (Total 27 min)
Reviews
- 5 stars79.16%
- 4 stars20.83%
TOP REVIEWS FROM BIG DATA SCIENCE WITH THE BD2K-LINCS DATA COORDINATION AND INTEGRATION CENTER
by MSJan 20, 2017
A very practical courses. Very good introduction to Big Data sources and Computational Analysis tool.
by JSMay 9, 2020
Excellent course! Thoroughly enjoyed learning from these excellent instructors. With very little prior knowledge on the topic, the course was quite easy to follow and very well explained!
by HHSep 18, 2018
excellent oppurtunity for the data science learners
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