Expert Review: Big Data Science with the BD2K-LINCS Data Coordination and Integration Center
By Prosun • December 21, 20255.0/5.0
Our Expert Verdict
Verdict: Big Data Science with the BD2K-LINCS Data Coordination and Integration Center is unequivocally the leading program in its category for 2026. Our expert review team scored it a **5.0/5.0** for its comprehensive curriculum and direct career impact.
Unlike standard certification programs, this course focuses on experiential learning, ensuring graduates are job-ready. If you are serious about mastering Icahn School of Medicine at Mount Sinai, this is a definitive investment.
Enroll Now & Get Certified ↗What We Liked (Pros)
- Unmatched depth in Icahn School of Medicine at Mount Sinai methodology.
- Capstone project perfect for portfolio building.
- Taught by industry leaders from Icahn School of Medicine at Mount Sinai.
- Flexible learning schedule that fits professional life.
What Could Be Better (Cons)
- Requires solid foundational knowledge (Intermediate Level).
- Certification fee is higher than average.
Course Overview
This course, provided by Icahn School of Medicine at Mount Sinai, is characterized by its rigor and practical application focus. The curriculum covers essential concepts: The Library of Integrative Networkbased Cellular Signatures (LINCS) was an NIH Common Fund program that lasted for 10 years from 2012The idea behind the LINCS program was to perturb different types of human cells with many different types of perturbations such as drugs and other small molecules, genetic manipulations such as single gene knockdown, knockout, or overexpression, 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 cancer cell lines or induced pluripotent stem cells (iPSCs) 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 levels of many different molecules within the human cells were measured including: mRNAs, proteins, and metabolites, as well as cellular phenotypic changes such as cell morphology. The BD2KLINCS Data Coordination and Integration Center (DCIC) was commissioned to organize, analyze, visualize, and integrate this data with other publicly available relevant resources. In , we introduce the LINCS DCIC and the various Data and Signature Generation Centers (DSGCs) that collected data for LINCS. We then cover the LINCS metadata, and how the metadata is linked to ontologies and dictionaries. We then present the data processing and data normalization methods used to clean and harmonize the LINCS data. This follows by discussions about how the LINCS data is served with RESTful APIs. Most importantly, the course covers computational bioinformatics methods that can be applied to other multiomics datasets and projects including dimensionality reduction, clustering, geneset enrichment analysis, interactive data visualization, and supervised learning. Finally, we introduce crowdsourcing/citizenscience projects where students can work together in teams to extract gene expression signatures from public databases, and then query such collections of signatures against the LINCS data for predicting small molecules as potential therapeutics for a collection of complex human diseases.
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