Big Data Science with LINCS: Bioinformatics & Data Analysis
Master bioinformatics and data analysis through the BD2K-LINCS program. Learn computational methods for analyzing multi-omics datasets and cellular signatures.
Master bioinformatics and data analysis through the BD2K-LINCS program. Learn computational methods for analyzing multi-omics datasets and cellular signatures.
This comprehensive course explores the Library of Integrative Network-based Cellular Signatures (LINCS) program and its applications in bioinformatics. Students learn about cellular perturbation analysis, data coordination, and integration techniques through the BD2K-LINCS Data Coordination and Integration Center. The curriculum covers essential topics including metadata management, RESTful APIs, bioinformatics pipelines, and advanced analytical methods such as dimensionality reduction, clustering, and machine learning. Participants gain hands-on experience with multi-omics datasets, interactive data visualization, and crowdsourcing projects for therapeutic discovery.
4.8
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What you'll learn
Understand the LINCS program and its applications in cellular signature analysis
Master metadata organization and ontology implementation
Develop skills in RESTful API usage and data integration
Learn advanced bioinformatics pipeline development and execution
Apply machine learning and clustering techniques to biological data
Create interactive data visualizations for complex datasets
Skills you'll gain
This course includes:
333 Minutes PreRecorded video
2 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 14 modules in this course
This comprehensive course introduces students to the Library of Integrative Network-based Cellular Signatures (LINCS) program and advanced bioinformatics methods. The curriculum covers essential aspects of big data analysis in biological systems, including metadata management, data normalization, and computational pipelines. Students learn practical skills in machine learning, enrichment analysis, and interactive data visualization, while exploring real-world applications in drug discovery and disease research. The course emphasizes hands-on experience with multi-omics datasets and modern computational tools.
The Library of Integrated Network-based Cellular Signatures (LINCS) Program Overview
Module 1 · 1 Hours to complete
Metadata and Ontologies
Module 2 · 25 Minutes to complete
Serving Data with APIs
Module 3 · 28 Minutes to complete
Bioinformatics Pipelines
Module 4 · 23 Minutes to complete
The Harmonizome
Module 5 · 46 Minutes to complete
Data Normalization
Module 6 · 28 Minutes to complete
Data Clustering
Module 7 · 43 Minutes to complete
Midterm Exam
Module 8 · 30 Minutes to complete
Enrichment Analysis
Module 9 · 28 Minutes to complete
Machine Learning
Module 10 · 36 Minutes to complete
Benchmarking
Module 11 · 25 Minutes to complete
Interactive Data Visualization
Module 12 · 1 Hours to complete
Crowdsourcing Projects
Module 13 · 18 Minutes to complete
Final Exam
Module 14 · 30 Minutes to complete
Fee Structure
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Instructor
Director, Mount Sinai Center for Bioinformatics Icahn School of Medicine at Mount Sinai
Dr. Avi Ma'ayan is a Professor in the Department of Pharmacological Sciences at the Icahn School of Medicine at Mount Sinai. He is also the Director of the Mount Sinai Center for Bioinformatics. Dr. Ma'ayan leads the NIH-funded BD2K-LINCS Data Coordination and Integration Center (DCIC) and the Mount Sinai Knowledge Management Center (KMC) for Illuminating the Druggable Genome (IDG). His research focuses on applying graph theory algorithms, machine learning, dynamical modeling, and visualization methods to integrate various -omics datasets from mammalian sources. This work aims to improve the understanding of biological regulation on a global scale.
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4.8 course rating
25 ratings
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