Related Experiment Video
Updated: Aug 14, 2026
07:58
Quantitative Imaging of Lineage-specific Toll-like Receptor-mediated Signaling in Monocytes and Dendritic Cells from Small Samples of Human Blood
Published on: April 16, 2012
Assessing the reliability of cellular decision making from noisy, multidimensional single-cell TNF-NF-κB signaling
Ali Emadi1, Tomasz Lipniacki2, Andre Levchenko3
1Arc Institute, Palo Alto, California, United States of America.
Plos Computational Biology
|August 12, 2026
Summary
This study introduces a Neyman-Pearson (NP) framework to analyze cell signaling noise, improving detection of abnormal responses and identifying pathological conditions. The NP method quantifies pathway performance from single-cell data.
Area of Science:
- Cellular signaling and decision-making under noisy conditions.
- Quantitative systems biology and statistical detection theory.
- Investigating NF-κB pathway dynamics in response to TNF.
Background:
- Cellular signaling abnormalities can lead to diseases.
- Accurate detection of signaling states is crucial for understanding cell fate.
- The NF-κB pathway plays a key role in cell survival, apoptosis, and immune responses.
Purpose of the Study:
- Develop a Neyman-Pearson (NP) detection-theory framework for analyzing single-cell measurements.
- Quantify the performance of cellular decision-making under varying conditions.
- Assess the impact of TNF dose and A20 deficiency on NF-κB signaling.
Main Methods:
- Applied NP detection framework to single-cell NF-κB response data in wild-type and A20-deficient fibroblasts stimulated with TNF.
- Modeled log-responses as Gaussian distributions to compute optimal thresholds, PD-PFA trade-offs, and ROC curves.
- Utilized both univariate (single time point) and bivariate (two time points) analyses.
- Validated findings using a non-parametric kernel-density detector on raw single-cell data.
Main Results:
- The NP framework successfully quantified detection probabilities (PD) for chosen false alarm probabilities (PFA).
- Increased TNF dose led to higher PD, and wild-type cells showed better performance than A20-/- cells.
- Combining data from two time points (30 minutes and 4 hours) significantly improved detection accuracy.
- Results confirmed expected biological responses and identified conditions where decision quality degraded.
Conclusions:
- The NP detection framework provides a robust and quantitative method to assess cellular pathway performance and identify failures.
- This approach transforms noisy single-cell data into actionable metrics for comparing experimental conditions.
- The framework can help elucidate mechanisms underlying cellular decision-making and its drift toward pathology.
