A Bayesian Treatment of the German Tank Problem

Simon, Cory

doi:10.1007/s00283-023-10274-6

Cited by 1 publication

(3 citation statements)

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“…To estimate the number of barcoded cancer cells using the German tank problem approach (Simon et al, 2023), we can adapt the mathematical model used in the original problem. In the German tank problem, the goal is to estimate the total number of items (tanks) based on observing a NGS sequence of serial numbers from a sample (Vogelstein et al, 2013).…”

Section: Methodsmentioning

confidence: 99%

“…Estimation Model: Develop a statistical model based on the German tank problem to estimate the total number of undetected cancer cells in each patient's samples (Simon et al, 2023). This model should consider the molecular barcode, time since treatment, and the known reference count.…”

Section: Methodsmentioning

confidence: 99%

“…Leveraging such techniques, our proposed study aims to estimate the number of undetected cancer cells post-treatment through a sampling-based approach. Inspired by the renowned German tank problem (Simon et al 2023), a method used during World War II to estimate enemy tank production based on captured serial numbers, our approach relies on the concept of statistical sampling to infer the total number of undetected cancer cells. By collecting serial samples from cancer patients at different time points following treatment, we can construct a unique molecular barcode that re ects the increasing number of mutations in cancerous cells over time.…”

Section: Introductionmentioning

confidence: 99%

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Unlocking the Genetic Enigma: Estimating the Hidden Horde of Barcoded Cancer Cells using a Molecular German Tank Problem Approach

TASTAN

2023

Preprint

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Accurate estimation of the number of undetected cancer cells after treatment is of paramount importance in oncology to gauge treatment efficacy and potential disease recurrence. Drawing inspiration from the German tank problem, we present a novel sampling-based molecular approach to estimate the population of elusive cancer cells that remain undetected by current molecular techniques. This study proposes an innovative approach to be undertaken in the future for estimating the number of undetected cancer cells post-treatment. Inspired by the renowned German tank problem, our sampling-based molecular methodology involves creating a unique molecular barcode representing the increasing mutations in cancerous cells over time. By collecting serial samples from cancer patients after treatment, we aim to statistically analyze and develop a robust estimation model to infer the total number of undetected cancer cells. The validation of this approach using an independent patient cohort would help ensure its reliability. Successful implementation of this methodology has the potential to revolutionize cancer research, providing crucial insights into residual cancer cell populations and facilitating the development of personalized treatment strategies. Ultimately, this future research endeavor could significantly impact cancer care, leading to improved patient outcomes and advancing our understanding of post-treatment cancer dynamics. This innovative approach may transform cancer research and improve patient outcomes by offering insights into the post-treatment cancer landscape that was hitherto concealed.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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