Mathematical modeling of a single-cell enzyme assay

1990 ◽  
Vol 35 (5) ◽  
pp. 525-532 ◽  
Author(s):  
K. Dane Wittrup ◽  
James E. Bailey
Keyword(s):  
Mathematical Modeling ◽  
Single Cell ◽  
Enzyme Assay ◽  
Cell Enzyme

scholarly journals Mathematical modeling with single-cell sequencing data

2019 ◽  
Author(s):  
Heyrim Cho ◽  
Russell C. Rockne
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Models ◽  
Single Cell ◽  
Myeloid Leukemia ◽  
State Transitions ◽  
Sequencing Data ◽  
Modeling Framework ◽  
Single Cell Sequencing ◽  
Cell State ◽  
Compare And Contrast

AbstractSingle-cell sequencing technologies have revolutionized molecular and cellular biology and stimulated the development of computational tools to analyze the data generated from these technology platforms. However, despite the recent explosion of computational analysis tools, relatively few mathematical models have been developed to utilize these data. Here we compare and contrast two approaches for building mathematical models of cell state-transitions with single-cell RNA-sequencing data with hematopoeisis as a model system; by solving partial differential equations on a graph representing discrete cell state relationships, and by solving the equations on a continuous cell state-space. We demonstrate how to calibrate model parameters from single or multiple time-point single-cell sequencing data, and examine the effects of data processing algorithms on the model calibration and predictions. As an application of our approach, we demonstrate how the calibrated models may be used to mathematically perturb normal hematopoeisis to simulate, predict, and study the emergence of novel cell types during the pathogenesis of acute myeloid leukemia. The mathematical modeling framework we present is general and can be applied to study cell state-transitions in any single-cell genome sequencing dataset.Author summaryHere we compare and contrast graph- and continuum-based approaches for constructing mathematical models of cell state-transitions using single-cell RNA-sequencing data. Using two publicly available datasets, we demonstrate how to calibrate mathematical models of hematopoeisis and how to use the models to predict dynamics of acute myeloid leukemia pathogenesis by mathematically perturbing the process of cellular proliferation and differentiation. We apply these modeling approaches to study the effects of perturbing individual or sets of genes in subsets of cells, or by modeling the dynamics of cell state-transitions directly in a reduced dimensional space. We examine the effects of different graph abstraction and trajectory inference algorithms on calibrating the models and the subsequent model predictions. We conclude that both the graph- and continuum-based modeling approaches can be equally well calibrated to data and discuss situations in which one method may be preferable over the other. This work presents a general mathematical modeling framework, applicable to any single-cell sequencing dataset where cell state-transitions are of interest.

scholarly journals PS1205 META-ANALYSIS USING DATA OF RED BLOOD CELL ENZYME ASSAY AND PROTEOME IN PATIENTS WITH DIAMOND-BLACKFAN ANEMIA

HemaSphere ◽  
2019 ◽  
Vol 3 (S1) ◽  
pp. 549
Author(s):  
T. Utsugisawa ◽  
T. Uchiyama ◽  
T. Aoki ◽  
A. Kinoshita ◽  
Y. Okamoto ◽  
...  
Keyword(s):  
Blood Cell ◽  
Red Blood Cell ◽  
Enzyme Assay ◽  
Meta Analysis ◽  
Diamond Blackfan Anemia ◽  
Cell Enzyme ◽  
Using Data

Single cell enzyme diagnosis on the chip

2013 ◽  
Author(s):  
Sissel Juul ◽  
Charlotte Harmsen ◽  
Maria Juul Nielsen ◽  
Magnus Stougaard ◽  
Kam W. Leong ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Enzyme

Multiple Sampling in Single-Cell Enzyme Assays Using CE-Laser-Induced Fluorescence to Monitor Reaction Progress

2005 ◽  
Vol 77 (10) ◽  
pp. 3132-3137 ◽  
Author(s):  
Glen K. Shoemaker ◽  
Justin Lorieau ◽  
Leon H. Lau ◽  
C. Stewart Gillmor ◽  
Monica M. Palcic
Keyword(s):  
Single Cell ◽  
Laser Induced Fluorescence ◽  
Enzyme Assays ◽  
Reaction Progress ◽  
Monitor Reaction ◽  
Multiple Sampling ◽  
Cell Enzyme

scholarly journals Monitoring and mathematical modeling of mitochondrial ATP in myotubes at single-cell level reveals two distinct population with different kinetics

2020 ◽  
Vol 8 (3) ◽  
pp. 228-237
Author(s):  
Naoki Matsuda ◽  
Ken-ichi Hironaka ◽  
Masashi Fujii ◽  
Takumi Wada ◽  
Katsuyuki Kunida ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Single Cell ◽  
Single Cell Level ◽  
Distinct Population ◽  
Cell Level
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