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In making advances within Computational Systems Biology there is an acknowledged need for the ongoing development of both probabilistic and mechanistic, possibly multi-scale, models of complex biological processes. In addition to such models the development of appropriate and efficient inferential methodology to identify and reason over such models is necessary.
Examples of the progress which has been made in our understanding of modern biology by the exploitation of such methodology include model based inference of p53 activity; uncovering the evolution of protein complexes and understanding the circadian clock in plants; details of which were presented at the LICSB workshops.
The previous workshop themes of parameter estimation, probabilistic modelling of networks and inference in large biological system models will be further explored in this meeting.
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Uploaded videos:
Keynote talks
Reconstructing networks from experimental and natural genetic perturbations
May 03, 2010
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4173 Views
Networking genes and drugs: Understanding gene function and drug mode of action ...
May 03, 2010
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4756 Views
Lectures
Estimating the contribution of non-genetic factors to gene expression using Gaus...
May 03, 2010
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3053 Views
Using sequential Monte Carlo approaches as a design tool in synthetic biology
May 03, 2010
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4304 Views
Decoding underlying behaviour from destructive time series experiments through G...
May 03, 2010
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2922 Views
Identifying interactions in the time and frequency domains in local and global n...
May 03, 2010
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3451 Views
Deterministic and stochastic models of bicoid protein gradient formation in Dros...
May 03, 2010
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3680 Views
Statistical analysis of protein patternation on cell membranes during immunologi...
May 06, 2010
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2623 Views
Machine learning methods for effective proteomics image analysis
May 03, 2010
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3890 Views