Workshop on Learning and Inference in Computational and Systems Biology (LICSB), London 2009
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.
Find out more at the Workshop website.
Gaussian process regression bootstrapping
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Bayesian Hypotheses Testing in Raman Spectroscopy
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Bayesian model selection: mechanistic models of Erk MAP kinase phosphorylation d...
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Temporal Development and Collapse of an Arctic Plant-Pollinator Network
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Role of Gene Mutations Predicted from a Computational Model of the Cochlea of th...
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Inference in a probabilistic model of dynamic DNA
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Genotyping Structural Variation
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Hybrid Inference for Stochastic Kinetic Models
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Opening - LICSB '09
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Time-varying genetic network inference using informative priors
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Estimation of Multiple Transcription Factor Activities using ODEs and Gaussian P...
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Detecting Evolutionary Inter-Gene Heterogeneity in Borrelia burgdorferi
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Moment closure and block updating for parameter inference in stochastic biologic...
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Definition of Valid Proteomic Biomarkers: Bayesian Solutions to a Currently Unme...
Apr 16, 2009 4060 views
Beyond Molecular Biology – Applying Gene Regulation Network Inference Methods in...
Apr 16, 2009 3967 views
Exploring experimental designs for network inference using perturbations and a B...
Apr 16, 2009 3104 views
