AutoRT: Deep Learning-Based Retention Time Prediction for Modified Peptides

Introducing AutoRT, a deep learning algorithm with high accuracy in retention time prediction for modified peptides. Genomics-based neoantigen discovery can be enhanced by proteomic evidence, but there remains a lack of consensus on the performance of different quality control methods for variant peptide identification in proteogenomics. Here, Bo Wen discusses how AutoRT can utilize the difference between accurately predicted and observed retention times for peptides as a metric to evaluate different quality control methods. ACCESS AutoRT: https://www.zhang-lab.org/software/ LEARN MORE ABOUT HOW PROTEOGENOMICS IS CHANGING CANCER RESEARCH Office of Cancer Clinical Proteomics Research Homepage: https://dctd.cancer.gov/programs/occpr Clinical Proteomic Tumor Analysis Consortium Info Page: https://dctd.cancer.gov/research/netw... VISUALS ARE INCLUSIVELY NARRATED  Important visual details are naturally described in this video’s main audio track. As such, a separate, audio-described version of this video is not provided.  LEARN MORE FROM THE NATIONAL CANCER INSTITUTE  Online: https://www.cancer.gov  By Phone: 1-800-4-CANCER (1-800-422-6237)  U.S. Department of Health and Human Services  National Institutes of Health  National Cancer Institute