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Big Data Science with the BD2K-LINCS Data Coordination and Integration Center
  • Level Professional
  • Duration 9 hours
  • Course by Icahn School of Medicine at Mount Sinai
  • Offered by

About

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.

Modules

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

    • 8 Videos
    • 2 Readings
    • 1 Discussion
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1 Discussions

  • LINCS L1000 Data - Practice Exercise

8 Videos

  • Layers of Cellular Regulation and Omics Technologies
  • The Connectivity Map
  • Geometrical View of the Connectivity Map Concept
  • LINCS Data and Signature Generation Centers
  • BD2K-LINCS Data Coordination and Integration Center
  • Induced Pluripotent Stem Cells (iPSCs)
  • Introduction to LINCS L1000 Data
  • L1000 Characteristic Direction Signature Search Engine (L1000CDS2) Demo

2 Readings

  • Syllabus
  • Grading and Logistics

Metadata and Ontologies

    • 2 Videos
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2 Videos

  • Introduction to Metadata and Ontologies | Part 1
  • Introduction to Metadata and Ontologies | Part 2

Serving Data with APIs

    • 2 Videos
    • 1 Discussion
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1 Discussions

  • Accessing Data through the Harmonizome's RESTful API - Practice Exercise

2 Videos

  • Accessing and Serving Data through RESTful APIs | Part 1
  • Accessing and Serving Data through RESTful APIs | Part 2

Bioinformatics Pipelines

    • 1 Videos
    • 1 Discussion
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1 Discussions

  • Bioinformatics Pipeline - Practice Exercise

1 Videos

  • Analyzing Big Data with Computational Pipelines

The Harmonizome

    • 4 Videos
    • 1 Discussion
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1 Discussions

  • Harmonizome - Practice Exercise

4 Videos

  • The Harmonizome Concept
  • Processing Datasets | Part 1
  • Processing Datasets | Part 2
  • Processing Datasets | Part 3

Data Normalization

    • 2 Videos
    • 1 Discussion
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1 Discussions

  • Data Normalization - Practice Exercise

2 Videos

  • Data Normalization | Part 1
  • Data Normalization | Part 2

Data Clustering

    • 3 Videos
    • 1 Discussion
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1 Discussions

  • Data Clustering - Practice Exercise

3 Videos

  • Data Clustering | Part 1 | Introduction
  • Data Clustering | Part 2 | Distance Functions
  • Data Clustering | Part 3 | Algorithms and Evaluation

Midterm Exam

    • 1 Assignment
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1 Assignment

  • Midterm Exam

Enrichment Analysis

    • 3 Videos
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3 Videos

  • Enrichment Analysis | Part 1
  • Enrichment Analysis | Part 2
  • Enrichr Demo

Introduction to Machine Learning

    • 3 Videos
    • 1 Discussion
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1 Discussions

  • Machine Learning - Practice Exercise

3 Videos

  • Introduction to Machine Learning | Part 1
  • Introduction to Machine Learning | Part 2
  • Introduction to Machine Learning | Part 3

Benchmarking

    • 2 Videos
    • 1 Discussion
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1 Discussions

  • Benchmarking - Practice Exercise

2 Videos

  • Benchmarking | Part 1
  • Benchmarking | Part 2

Interactive Data Visualization

    • 4 Videos
    • 1 Discussion
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1 Discussions

  • Visualizing Gene Expression Data using Interactive Clustergrams Built with D3.js - Practice Exercise

4 Videos

  • Interactive Data Visualization with E-Charts
  • Visualizing Data using Interactive Clustergrams Built with D3.js | Part 1
  • Visualizing Data using Interactive Clustergrams Built with D3.js | Part 2
  • Visualizing Data using Interactive Clustergrams Built with D3.js | Part 3

Crowdsourcing Projects

    • 2 Videos
    • 1 Readings
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2 Videos

  • Microtasks and GEO2Enrichr Demo
  • L1000-2-P100 Megatask Challenge

1 Readings

  • BD2K-LINCS DCIC Crowdsourcing Portal

Final Exam

    • 1 Assignment
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1 Assignment

  • Final Exam

Auto Summary

Embark on a journey through the cutting-edge world of big data science with the BD2K-LINCS Data Coordination and Integration Center course. Tailored for professionals in the Science & Engineering domain, this comprehensive course delves into the NIH Common Fund's LINCS program, which spanned a decade from 2012 to 2021. Learn how the program applied various perturbations—such as drugs, genetic manipulations, and environmental conditions—to different human cells, including cancer cell lines and iPSCs, to explore the resulting molecular network changes. The course offers an in-depth understanding of the BD2K-LINCS DCIC's role in organizing, analyzing, visualizing, and integrating the extensive data collected, along with insights into the different Data and Signature Generation Centers (DSGCs). You'll gain hands-on experience with LINCS metadata, data processing, normalization methods, and the use of RESTful APIs for data serving. Moreover, the course introduces pivotal computational bioinformatics techniques, such as dimensionality reduction, clustering, gene-set enrichment analysis, interactive data visualization, and supervised learning. As a highlight, participate in crowdsourcing and citizen-science projects to extract gene expression signatures and predict potential therapeutics for complex human diseases. Offered by Coursera, this professional-level course spans 540 minutes and is available under Starter and Professional subscription plans, making it an ideal choice for professionals eager to advance their expertise in big data science and bioinformatics.

Avi Ma’ayan, PhD
Instructor

Avi Ma’ayan, PhD