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

Learner Reviews & Feedback for Big Data Science with the BD2K-LINCS Data Coordination and Integration Center by Icahn School of Medicine at Mount Sinai

4.8
stars
25 ratings

About the Course

The Library of Integrative Network-based Cellular Signatures (LINCS) was an NIH Common Fund program that lasted for 10 years from 2012-2021. The idea behind the LINCS program was to perturb different types of human cells with many different types of perturbations such as drugs and other small molecules, genetic manipulations such as single gene knockdown, knockout, or overexpression, 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 cancer cell lines or induced pluripotent stem cells (iPSCs) 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 levels of many different molecules within the human cells were measured including: mRNAs, proteins, and metabolites, as well as cellular phenotypic changes such as cell morphology. The BD2K-LINCS Data Coordination and Integration Center (DCIC) was commissioned to organize, analyze, visualize, and integrate this data with other publicly available relevant resources. In this course, we introduce the LINCS DCIC and the various Data and Signature Generation Centers (DSGCs) that collected data for LINCS. We then cover the LINCS metadata, and how the metadata is linked to ontologies and dictionaries. We then present the data processing and data normalization methods used to clean and harmonize the LINCS data. This follows by discussions about how the LINCS data is served with RESTful APIs. Most importantly, the course covers computational bioinformatics methods that can be applied to other multi-omics datasets and projects including dimensionality reduction, 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 gene expression signatures from public databases, and then query such collections of signatures against the LINCS data for predicting small molecules as potential therapeutics for a collection of complex human diseases....

Top reviews

JS

May 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!

MS

Jan 20, 2017

A very practical courses. Very good introduction to Big Data sources and Computational Analysis tool.

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1 - 8 of 8 Reviews for Big Data Science with the BD2K-LINCS Data Coordination and Integration Center

By Tomas R

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Feb 24, 2020

This course provides a great overview of the BD2K-LINCS program and demonstrates that it's possible to combine multiple (not very related datasets) to bring new biological insights. Some of these concepts are directly relevant to my job.

I am giving only 4 stars because is seems to me that some later parts of the course are not fully relevant to the overall topic. It would be also very useful to provide several "success stories" how the data was used to; for example, initiate drug discovery.

By Jaspreet S P

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Mar 22, 2020

This was a great course getting into the practical domain of the computational biology side. The lecturer was great. But certain topics were brief and the practical assessment test was more focused on different languages like R, JSON, Python and many more. So it is not possible to be jack of all trades. Also everything was perfectly woven with the LINCS project. Kudos to everyone involved in the project.

By Musalula S

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Jan 21, 2017

A very practical courses. Very good introduction to Big Data sources and Computational Analysis tool.

By Jacqulene P S S

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May 10, 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 Jose M V

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Jul 29, 2017

I recommend it, good materials, very instructive and a good level. Very interesting course.

By Dong A

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Oct 25, 2022

Great class even if I failed to use GEO2Enchir but I used GEO2R to get the answers.

By Nagasai H

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Sep 19, 2018

excellent oppurtunity for the data science learners

By Ezra L

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Feb 27, 2018

Fun, fascinating, and informative!