Big Data Science with the BD2K-LINCS Data Coordination and Integration Center
- Offered byCoursera
Big Data Science with the BD2K-LINCS Data Coordination and Integration Center at Coursera Overview
Duration | 9 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
Big Data Science with the BD2K-LINCS Data Coordination and Integration Center at Coursera Highlights
- 33% got a tangible career benefit from this course.
- 50% got a pay increase or promotion.
- Earn a shareable certificate upon completion.
Big Data Science with the BD2K-LINCS Data Coordination and Integration Center at Coursera Course details
- 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.
Big Data Science with the BD2K-LINCS Data Coordination and Integration Center at Coursera Curriculum
The Library of Integrated Network-based Cellular Signatures (LINCS) Program Overview
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
Syllabus
Grading and Logistics
Introduction to Metadata and Ontologies
Part 1
Introduction to Metadata and Ontologies
Part 2
Accessing and Serving Data through RESTful APIs
Part 1
Accessing and Serving Data through RESTful APIs
Part 2
Bioinformatics Pipelines
Analyzing Big Data with Computational Pipelines
The Harmonizome Concept
Processing Datasets
Part 1
Processing Datasets
Part 2
Processing Datasets
Part 3
Data Normalization
Data Normalization
Part 1
Data Normalization
Part 2
Data Clustering
Part 1
Introduction
Data Clustering
Part 2
Distance Functions
Data Clustering
Part 3
Algorithms and Evaluation
Midterm Exam
Enrichment Analysis
Enrichment Analysis
Part 1
Enrichment Analysis
Part 2
Enrichr Demo
Introduction to Machine Learning
Part 1
Introduction to Machine Learning
Part 2
Introduction to Machine Learning
Part 3
Benchmarking
Benchmarking
Part 1
Benchmarking
Part 2
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
Microtasks and GEO2Enrichr Demo
L1000-2-P100 Megatask Challenge
BD2K-LINCS DCIC Crowdsourcing Portal
Final Exam
Final Exam
Big Data Science with the BD2K-LINCS Data Coordination and Integration Center at Coursera Admission Process
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