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| Name | ConnectivityMap Query tutorial | clue.io | LINCS | CMap L1000 Assay | Differential Gene Expression |
| Video Uploader | Video From Cell Kulture Co. |
| Upload Date | This Video Uploaded At 26-03-2022 01:28:04 |
| Video Discription | In this experiment tutorial, I’ll be showing you how to create and interpret a gene expression heat map with the clue.io ConnectivityMap (CMap) Query application. WHAT YOU'LL NEED: - Internet access - Web browser - A list of differentially expressed genes The ConnectivityMap (CMap) is a free resource that uses cellular responses to perturbation to find relationships (“connections”) between diseases, genes, and therapeutics. The CMap database contains over one million gene expression signatures from the treatment of a variety of cell types with a range of perturbagens, including small-molecule compounds, and gene overexpression or knockdown reagents. Changes in gene expression that arise from a disease or perturbagen treatment can be compared for similarity to all perturbational signatures in the CMap database. Perturbations with highly similar gene expression signatures are termed “connected” and their similar transcriptional effects suggest they have related physiological effects on the cell. The connections identified in CMap analysis can be used to develop hypotheses for disease treatments. For the purpose of this tutorial, we will be using CMap to analyze differentially expressed gene lists, with the goal of identifying the potential mode of action or target of an experimental compound. We’ll accomplish this by using the ConnectivityMap Query application to assess for connectivity between the differentially expressed genes that result from treatment with our experimental drug to known compounds and perturbations in the CMap database. TABLE OF CONTENTS: 00:00 What is the ConnectivityMap? 03:19 Creating an account 04:05 How to use the Query app 05:10 The L1000 gene expression assay 08:32 Uploading gene expression data 11:48 Analyzing gene expression data 22:53 Helpful technical resources |
| Category | Education |
| Tags | broad institute | drug discovery | gene expression | drug discovery and development | drug discovery process | drug discovery medicinal chemistry | drug discovery machine learning | drug discovery and development in pharmacology | drug discovery and development medicinal chemistry | drug discovery and drug design | gene expression and regulation | gene expression in eukaryotes | gene expression analysis | computational biology lecture | computational biology and bioinformatics |
