About
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.
Videos
Welcome

Introduction
Apr 17, 2008
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3192 views
Session 1

Gaussian process modelling of transcription factor networks using Markov Chain M...
Apr 17, 2008
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4507 views

Time delay analysis
Apr 17, 2008
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5658 views

Gaussian process modelling of latent chemical species: Applications to inferring...
Apr 17, 2008
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3131 views

Data variability could be your friend
Apr 17, 2008
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5487 views
Session 2

Statistical learning of biological networks: a brief overview
Apr 17, 2008
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4497 views

Relationship between structure and dynamics of gene regulatory networks
Apr 17, 2008
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5526 views

Learning Bayesian networks from postgenomic data with an improved structure MCMC...
Apr 17, 2008
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5948 views

Validating inferred gene networks using ODE models of regulation dynamics
Apr 17, 2008
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4193 views
Session 3

Parameter estimation using moment-closure methods
Apr 17, 2008
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4366 views

BioBayes: Bayesian inference for Systems Biology
Apr 17, 2008
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419140 views

Abductive and inductive inference for integrative Systems Biology
Sep 4, 2019
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1 views

Parameter estimation in biochemical reaction networks: An observer-based approac...
Apr 17, 2008
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3852 views
Session 4

Probabilistic multi-class multi-kernel learning: On protein fold recognition and...
Apr 17, 2008
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4145 views

Predicting anti-cancer molecule activity using machine learning algorithms
Apr 17, 2008
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419362 views

Factor models for QTL studies
Apr 17, 2008
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5398 views