Big Data Science with the BD2K-LINCS Data Coordination and Integration Center
- 4.8
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Course Summary
This course is about the use of large-scale experiments in biology and the analysis of data generated from these experiments.Key Learning Points
- Learn about the use of large-scale experiments in biology
- Understand how to analyze data from these experiments
- Discover the potential applications of this type of research
Related Topics for further study
Learning Outcomes
- Understand the use of large-scale experiments in biology
- Analyze data generated from these experiments
- Apply this knowledge to potential research projects
Prerequisites or good to have knowledge before taking this course
- Basic understanding of biology
- Familiarity with statistical analysis
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
Similar Courses
- Biological Data Analysis Using R
- Data Analysis and Interpretation Specialization
Related Education Paths
Related Books
Description
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.
Outline
- 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
- Metadata and Ontologies
- Introduction to Metadata and Ontologies | Part 1
- Introduction to Metadata and Ontologies | Part 2
- Serving Data with APIs
- 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
- 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
- Data Clustering | Part 1 | Introduction
- Data Clustering | Part 2 | Distance Functions
- Data Clustering | Part 3 | Algorithms and Evaluation
- Midterm Exam
- Midterm Exam
- Enrichment Analysis
- Enrichment Analysis | Part 1
- Enrichment Analysis | Part 2
- Enrichr Demo
- Machine Learning
- 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
- 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
Summary of User Reviews
BD2K-LINCS is a highly recommended course by users who found it to be informative and engaging. Many users appreciated the course's comprehensive coverage of the LINCS project and its potential applications in drug discovery. Overall, users rated the course highly for its quality content and engaging delivery style.Key Aspect Users Liked About This Course
Comprehensive coverage of the LINCS project and its potential applications in drug discoveryPros from User Reviews
- Quality content
- Engaging delivery style
- Informative
- Excellent resource for drug discovery professionals
- Great learning experience
Cons from User Reviews
- Some lectures can be dry
- Requires a strong background in biology and computer science
- Course material can be challenging to digest
- Lack of interaction with instructors
- Not suitable for beginners
Avi Ma’ayan, PhD
4.8 Raiting
Big Data Science with the BD2K-LINCS Data Coordination and Integration Center
- 4.8
-
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The Library of Integrative Network-based Cellular Signatures (LINCS) is an NIH Common Fund program. We then cover metadata and how metadata is linked to ontologies....
