Virtual patient analysis identifies strategies to improve the performance of predictive biomarkers for PD-1 blockade

Name: Virtual patient analysis identifies strategies to improve the performance of predictive biomarkers for PD-1 blockade
Creator: Theinmozhi Arulraj
Published: 2024-10-14T08:04:09.995Z
Keywords: Cancer Immunotherapy, Breast Cancer, Computational Biology, Biomarker Discovery

Arulraj, Theinmozhi; Wang, Hanwen; Deshpande, Atul; Varadhan, Ravi; Emens, Leisha A.; Jaffee, Elizabeth M.; Fertig, Elana J.; Santa-Maria, Cesar A.; Popel, Aleksander S.

doi:10.17632/77wpsgr8ch.1

Virtual patient analysis identifies strategies to improve the performance of predictive biomarkers for PD-1 blockade

Published: 14 October 2024| Version 1 | DOI: 10.17632/77wpsgr8ch.1

Contributors:

Theinmozhi Arulraj, Hanwen Wang, Atul Deshpande, Ravi Varadhan, Leisha A. Emens, Elizabeth M. Jaffee, Elana J. Fertig, Cesar A. Santa-Maria, Aleksander S. Popel

Description

This repository contains the computational code for biomarker testing algorithm developed by the Popel Systems Biology Laboratory. https://popellab.johnshopkins.edu/.

Files

Steps to reproduce

Refer the readme file

Institutions

Johns Hopkins University

Funding

National Institutes of Health

R01CA138264

Virtual patient analysis identifies strategies to improve the performance of predictive biomarkers for PD-1 blockade

Description

Files

Steps to reproduce

Institutions

Categories

Funding

Licence