Abstract
Simultaneous dynamic profiling of mRNA and protein expression is increasingly popular, and there is a critical need for algorithms to identify regulatory layers and time dependency of gene expression. A group of scientists from United States and Singapore present PECAplus, a comprehensive set of statistical analysis tools to address this challenge. Protein expression control analysis (PECA) computes the probability scores for change in mRNA and protein-level regulatory parameters at each time point, deconvoluting gene expression regulation in the presence of measurement noise. PECAplus adapted PECA’s mass action model to a variety of proteomic data including pulsed SILAC and generic protein expression data. It also features analysis modules to fit smooth curves on rugged time series observations, and to facilitate time-dependent interpretation of the data for genes and biological functions. They demonstrate the core modules with two time course datasets of mammalian cells responding to unfolded proteins and pathogens.
| Original language | English (US) |
|---|---|
| Article number | 3 |
| Journal | npj Systems Biology and Applications |
| Volume | 4 |
| Issue number | 1 |
| DOIs | |
| State | Published - Dec 1 2018 |
Fingerprint
ASJC Scopus subject areas
- Computer Science Applications
- Applied Mathematics
- Modeling and Simulation
- Biochemistry, Genetics and Molecular Biology(all)
- Drug Discovery
Cite this
PECAplus : statistical analysis of time-dependent regulatory changes in dynamic single-omics and dual-omics experiments. / Teo, Guoshou; Bin Zhang, Yun; Vogel, Christine; Choi, Hyungwon.
In: npj Systems Biology and Applications, Vol. 4, No. 1, 3, 01.12.2018.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - PECAplus
T2 - statistical analysis of time-dependent regulatory changes in dynamic single-omics and dual-omics experiments
AU - Teo, Guoshou
AU - Bin Zhang, Yun
AU - Vogel, Christine
AU - Choi, Hyungwon
PY - 2018/12/1
Y1 - 2018/12/1
N2 - Simultaneous dynamic profiling of mRNA and protein expression is increasingly popular, and there is a critical need for algorithms to identify regulatory layers and time dependency of gene expression. A group of scientists from United States and Singapore present PECAplus, a comprehensive set of statistical analysis tools to address this challenge. Protein expression control analysis (PECA) computes the probability scores for change in mRNA and protein-level regulatory parameters at each time point, deconvoluting gene expression regulation in the presence of measurement noise. PECAplus adapted PECA’s mass action model to a variety of proteomic data including pulsed SILAC and generic protein expression data. It also features analysis modules to fit smooth curves on rugged time series observations, and to facilitate time-dependent interpretation of the data for genes and biological functions. They demonstrate the core modules with two time course datasets of mammalian cells responding to unfolded proteins and pathogens.
AB - Simultaneous dynamic profiling of mRNA and protein expression is increasingly popular, and there is a critical need for algorithms to identify regulatory layers and time dependency of gene expression. A group of scientists from United States and Singapore present PECAplus, a comprehensive set of statistical analysis tools to address this challenge. Protein expression control analysis (PECA) computes the probability scores for change in mRNA and protein-level regulatory parameters at each time point, deconvoluting gene expression regulation in the presence of measurement noise. PECAplus adapted PECA’s mass action model to a variety of proteomic data including pulsed SILAC and generic protein expression data. It also features analysis modules to fit smooth curves on rugged time series observations, and to facilitate time-dependent interpretation of the data for genes and biological functions. They demonstrate the core modules with two time course datasets of mammalian cells responding to unfolded proteins and pathogens.
UR - http://www.scopus.com/inward/record.url?scp=85052712570&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85052712570&partnerID=8YFLogxK
U2 - 10.1038/s41540-017-0040-1
DO - 10.1038/s41540-017-0040-1
M3 - Article
AN - SCOPUS:85052712570
VL - 4
JO - npj Systems Biology and Applications
JF - npj Systems Biology and Applications
SN - 2056-7189
IS - 1
M1 - 3
ER -