Course Description

Library of Integrative Network-based Cellular Signatures (LINCS) Overview

LINCS Program Overview

The Library of Integrative Network-based Cellular Signatures (LINCS) is an NIH Common Fund program. It aims to perturb different types of human cells using various perturbations such as drugs, genetic manipulations, and microenvironmental changes. These perturbations are applied to human cells, including induced pluripotent stem cells differentiated into lineages like neurons and cardiomyocytes. The program measures changes in mRNAs, proteins, metabolites, and cellular phenotypes to understand affected molecular networks.

BD2K-LINCS Data Coordination and Integration Center (DCIC)

The BD2K-LINCS DCIC organizes, analyzes, visualizes, and integrates this data with other publicly available resources. The course covers the DCIC and the various Centers that collect data for LINCS.

What You Will Learn

  1. LINCS Program Overview
  • Introduction to the LINCS concept
  • Tutorials on using the LINCS L1000 dataset
  1. Metadata and Ontologies
  • High-level concepts of metadata and ontologies
  • Application to LINCS datasets
  1. Serving Data with APIs
  • Accessing data through application programming interfaces (APIs)
  1. Bioinformatics Pipelines
  • Concepts of bioinformatics pipelines
  1. The Harmonizome
  • Integration of resources containing knowledge about genes and proteins
  • Available as a web-server application at: Harmonizome
  1. Data Normalization
  • Mathematical concepts behind data normalization
  1. Data Clustering
  • Unsupervised learning and pattern identification in data
  1. Midterm Exam
  • 45 multiple choice questions covering modules 1-7
  • Includes practical analysis with learned methods
  1. Enrichment Analysis
  • Performing gene set enrichment analyses
  • Querying gene sets from genomics and proteomics studies against annotated gene sets
  1. Machine Learning
    • Mathematical concepts of supervised machine learning
    • Making predictions from examples associating observations/features with properties to learn/predict
  2. Big Data Science with BD2K-LINCS DCIC
    • Free Course on big data science with BD2K-LINCS DCIC

Keywords to Focus On

  • LINCS program
  • induced pluripotent stem cells
  • gene set enrichment analysis
  • supervised machine learning
  • bioinformatics pipelines
  • data normalization
  • data clustering
  • metadata and ontologies
  • APIs for data access

Meta Description

Learn about the Library of Integrative Network-based Cellular Signatures (LINCS) program, its perturbation techniques, data coordination by BD2K-LINCS DCIC, and key bioinformatics concepts including data normalization, clustering, enrichment analysis, and machine learning. Discover the Harmonizome project and how to access data via APIs.

Additional Tips for SEO

  1. Title Tag: Ensure your page title includes primary keywords like "LINCS Program", "Bioinformatics", "Machine Learning", and "Data Normalization".
  2. Headings: Use descriptive headings (H1, H2, H3) that include relevant keywords.
  3. Internal Links: Link to related content within your website to improve navigation and SEO.
  4. External Links: Include reputable external links like the Harmonizome link provided.
  5. Mobile Optimization: Ensure the content is mobile-friendly as Google prioritizes mobile-first indexing.
  6. Alt Text for Images: If including images, use descriptive alt text with keywords.
  7. Meta Keywords: Include keywords in the meta keywords tag (though less important, it can still be useful).

By incorporating these SEO strategies, you can improve the visibility and ranking of your content in search engine results.