Estimating Clonal Dynamics Using Coalescent Theory and Branching Processes
Explore a 39-minute lecture on estimating clonal dynamics through coalescent theory and branching processes, delivered by Kit Curtius from the University of California, San Diego. Delve into the intersection of mathematics and oncology as part of the Fie…
Decoding Evolutionary Information from Cancer Trees
Explore a 41-minute lecture on decoding evolutionary information from cancer trees, presented by Alison Feder from the University of Washington, Seattle. Delve into the intersection of oncology and evolutionary biology as part of the Thematic Program on…
Defining Selection in Somatic Evolution by Modeling Tumor-Stromal Interactions
Explore the complex dynamics of tumor-stromal interactions and their role in somatic evolution through a 35-minute lecture by David Basanta from Moffitt Cancer Center. Delve into the fascinating field of mathematical oncology as part of the Thematic Prog…
Personalized Cancer Care through Digital Twin Technology: Integrating Patient-Specific Data with Quantitative Systems Pharmacology
Explore a cutting-edge lecture on the integration of digital twin technology with quantitative systems pharmacology for personalized cancer care. Delve into the innovative approach presented by Leili Shahriyari from the University of Massachusetts Amhers…
Mechanistic Learning Reveals Cell Fate Transitions Driving B-Cell Acute Lymphoblastic Leukemia Progression
Explore a 42-minute conference talk from the Fields Institute's Thematic Program on Mathematical Oncology, focusing on mechanistic learning in B-cell acute lymphoblastic leukemia. Delivered by Jeffrey West from Moffitt Cancer Center, the presentation del…
Fighting Drug Resistance with Math
Explore a compelling lecture on combating drug resistance through mathematical approaches. Delve into the innovative research presented by Doron Levy from the University of Maryland College Park as part of the Thematic Program on Mathematical Oncology. G…
Evolutionary Rescue as a Framework for Understanding Drug Resistance in Cancer
Explore evolutionary rescue's role in cancer drug resistance, examining its impact on treatment strategies and tumor adaptation.
Combining Machine Learning and Modeling Approaches to Forecasting Disease Progression
Explore innovative forecasting techniques for disease progression by integrating machine learning with modeling approaches in this cutting-edge presentation.
Genetic Composition of Supercritical Branching Populations Under Power Law Mutation Rate
Explore genetic composition in supercritical branching populations, focusing on power law mutation rates and their implications for evolutionary dynamics.
Sensitivity, Spatial Models, and Fokker-Planck Equations in Mathematical Oncology - Graduate Course
Dive into advanced mathematical concepts in oncology, exploring sensitivity analysis, spatial modeling, and Fokker-Planck equations with Dr. Thomas Hillen.
A Method to Coarse-Grain Multi-Agent Stochastic Systems with Regions of Multistability
Dive into a mathematical oncology seminar exploring coarse-graining techniques for multi-agent stochastic systems, focusing on regions of multistability in cancer modeling.
Can Gut Reactor Models Play a Role in Mathematical Oncology?
Explore the potential role of gut reactor models in mathematical oncology through Hermann Eberl's seminar on innovative approaches to cancer research.
Parameter Estimation in Mathematical Oncology - Lecture
Dive into advanced techniques for parameter estimation in mathematical oncology, exploring key concepts and practical applications.
Cancer Stem Cells - Part II
Dive into advanced concepts of cancer stem cells with Dr. Natalia Komarova, exploring cutting-edge research and theories in mathematical oncology.
Understanding Chemotherapeutic Tolerance Through a Mathematical Model of Drug-Induced Resistance
Explore a mathematical model of drug-induced resistance in cancer treatment, examining chemotherapeutic tolerance and its implications for oncology.
Challenges in the Use of Virtual Populations for Oncology Drug Development
Explore challenges in using virtual populations for oncology drug development, focusing on mathematical modeling and optimization techniques.
Enhanced Therapeutic Effects and Safety Profile of Systemically Delivered Oncolytic Adenovirus
Explore advancements in oncolytic adenovirus therapy, focusing on improved efficacy and safety for systemic delivery in cancer treatment.
Computational Methods for Inferring Tumor Evolution and Heterogeneity
Explore computational techniques for analyzing tumor evolution and heterogeneity, enhancing understanding of cancer progression and treatment strategies.
Quantifying CAR T Cells Activity Against AML - Model Selection Based on In Vitro Cytolytic Assays
Explore quantitative modeling of CAR T cell activity against AML through in vitro cytolytic assays, enhancing understanding of immunotherapy effectiveness.
Biophysical Modeling of Tumor-Immune Interactions for Optimizing T-Cell Immunotherapy
Explore biophysical modeling techniques for tumor-immune interactions to enhance T-cell immunotherapy effectiveness and optimize treatment strategies.
Quantifying Tumor Heterogeneity Across Space and Time
Explore advanced techniques for analyzing tumor heterogeneity spatially and temporally with Dr. Ben Raphael's in-depth presentation on cutting-edge mathematical oncology approaches.