Benign or cancerous? Identifying mutation types with machine learning

Machine Learning


Live Symposium

Monday, June 19, 2023
11:00 AM – 2:00 PM ET

Tumors are molecular and cellular mosaics that acquire numerous mutations. Scientists are trying to identify tumorigenic mutations among thousands of other genetic differences to help clinicians predict treatment and survival outcomes for different types of cancer.

At this symposium, the scientistCreative Services team at , researchers discuss precise genomic and transcriptome profiling in cancer clinics and how big data approaches help scientists understand patient data in real time .

Symposium program

11:00 am – Introduction

11:10 am – Spatial transcriptomics analysis of neoadjuvant immunotherapy in gastrointestinal cancer

Lucien Tsukamoto Kagohara PhD

11:45am – TBA

Elana J. Fertig, PhD, FAIMBE

12:20 PM – Proteomic Approaches to Streamline Anticancer Drug Responses: Towards the Next Generation of Precision Medicine

Dr. Pedro R. Cutillas

1:30 PM – Open panel Q&A session
Deana McNeil scientist’s The Creative Services team will participate in an open Q&A session with the entire panel, where presenters will answer questions posed by the audience.

Lisa

Lucien Tsukamoto Kagohara PhD
Associate Professor
Sidney Kimmel Comprehensive Cancer Center
Johns Hopkins University

Sun Jie

Elana J. Fertig, PhD, FAIMBE
Division Director and Associate Cancer Center Director, Quantitative Science
Co-Director, Convergence Institute
Co-Director, Single Cell Training and Analysis Center (STAC)
Daniel Nathans Scientific Innovator
Professor
Oncology, Biomedical Engineering, Applied Mathematics and Statistics
Johns Hopkins University

Katla

Dr. Pedro R. Cutillas
Professor, Cell Signaling and Proteomics
Center for Genomics and Computational Biology
Barts Cancer Institute – UK Center of Excellence for Cancer Research
Queen Mary University London

organizer



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