Cancer Data Science Pulse
Using Cancer Data Science to Advance Your Research
Data, Clinical Trials, and You
Performing a CIViC Duty—A Community-Driven Resource for Interpreting Data on Cancer Variants
If you’re planning to set up a clinical trial, you can use the information in this blog to help you determine your baselines and parameters. See what’s been done with different therapeutics and the outcomes before you set up your trial! You’ll also learn about CIViC, an open-source platform that connects researchers to the latest published findings on a wide range of cancer variant interpretations.
Making Sense of Data Sharing (and Management)
Your Guide to the 2023 NIH Data Management and Sharing Policy
Whether you’re new to
Funding for
Discover the New Index of NCI Studies Web Application to Get NCI Research Outputs
If you’re looking for examples of how NCI funding could help support
NCI-Funded Partnership Uses AI to Improve Diversity in Cancer Clinical Trials
Are you passionate about improving diversity in clinical trials?
You’ve Got Data! Now What?
Visualizing Data Using Circular Heatmaps and Biplots—Pro-Tips from NCI Researchers
Are you comfortable with the basics of
Collaboration is Key
Federated Learning – A Solution for Democratizing Data for Cancer Research?
Does the scope of
Resource/Tool Name |
What is it? |
What does it do? |
How can you use it? |
Software |
The ATOM Modeling PipeLine (AMPL) is an open source, modular, extensive software pipeline for building and sharing models. |
Use AMPL to generate machine learning models for your work in advancing silico drug discovery. |
|
Software |
CANcer Distributed Learning Environment (CANDLE) is an open source software platform that improves prediction accuracy of machine learning algorithms. |
Explore CANDLE to find resources that help with hyperparameter optimization for more accurate machine learning in your cancer research. |
|
Program |
Informatics Technology for Cancer Research (ITCR) is an NCI-program supporting informatics technology across cancer research. |
Visit this website to discover the wide range of tools in the ITCR portfolio. You can use these tools for your work in omics, imaging, network biology, clinical research, and data standards. |
|
Data Set |
This provides dataframes (e.g., gene expression and drug response data, etc.) and supporting metadata used in the Pilot 1 project. |
Check out this resource if you’re looking into systematically modeling tumor drug response with deep learning models more suited for large-scale data. |
Are there additional topics you’d like to see covered to help you understand what
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Michael Isaac Lerman on April 21, 2023 at 10:45 a.m.