Development of a high-throughput quantitative immunofluorescence method and stochastic modeling of signalling networks
Lead Research Organisation:
Imperial College London
Department Name: Life Sciences
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Organisations
People |
ORCID iD |
| Michael Stumpf (Principal Investigator) |
Publications
Ale A
(2013)
A general moment expansion method for stochastic kinetic models.
in The Journal of chemical physics
Filippi S
(2016)
Robustness of MEK-ERK Dynamics and Origins of Cell-to-Cell Variability in MAPK Signaling.
in Cell reports
Harrington HA
(2012)
Parameter-free model discrimination criterion based on steady-state coplanarity.
in Proceedings of the National Academy of Sciences of the United States of America
Harrington HA
(2013)
Cellular compartments cause multistability and allow cells to process more information.
in Biophysical journal
Jetka T
(2014)
StochDecomp--Matlab package for noise decomposition in stochastic biochemical systems.
in Bioinformatics (Oxford, England)
Komorowski M
(2013)
Decomposing Noise in Biochemical Signaling Systems Highlights the Role of Protein Degradation
in Biophysical Journal
Komorowski M
(2012)
StochSens--Matlab package for sensitivity analysis of stochastic chemical systems.
in Bioinformatics (Oxford, England)
Komorowski M
(2011)
Sensitivity, robustness, and identifiability in stochastic chemical kinetics models.
in Proceedings of the National Academy of Sciences of the United States of America
Lakatos E
(2015)
Multivariate moment closure techniques for stochastic kinetic models.
in The Journal of chemical physics
Liepe J
(2014)
A framework for parameter estimation and model selection from experimental data in systems biology using approximate Bayesian computation.
in Nature protocols
| Description | We are now able to understand how signals flow through eukaryotic cells much better. |
| Exploitation Route | We have received an HFSP grant and several fellowships which continue the collaboration with Japan. |
| Sectors | Agriculture Food and Drink Healthcare Pharmaceuticals and Medical Biotechnology |
| Description | This has been a phenomenal research training opportunity and allowed most members of my group to spend some time in a leading international systems biology experimental group. We have also gained much better understanding of how signalling across MAPK works. |
| First Year Of Impact | 2011 |
| Sector | Agriculture, Food and Drink,Digital/Communication/Information Technologies (including Software),Education,Healthcare,Pharmaceuticals and Medical Biotechnology |
| Impact Types | Cultural Economic Policy & public services |
| Title | InformationMeasures.jl |
| Description | A Julia package to infer gene regulatory networks using information theoretical approaches. |
| Type Of Technology | Software |
| Year Produced | 2016 |
| Impact | This is a very fast (up to 500 times faster than current R packages) and accurate means of applying bi- and multi-variate information theoretical measures. |
| URL | https://github.com/Tchanders/InformationMeasures.jl |