Learning and Inference in Computational Systems Biology (LICSB), Warwick 2010

Learning and Inference in Computational Systems Biology (LICSB), Warwick 2010

9 Lectures · Mar 30, 2010

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.

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

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46:42

Reconstructing networks from experimental and natural genetic perturbations

Florian Markowetz

May 03, 2010

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4174 Views

Keynote
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50:15

Networking genes and drugs: Understanding gene function and drug mode of action ...

Diego di Bernardo

May 03, 2010

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4758 Views

Keynote

Lectures

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11:15

Estimating the contribution of non-genetic factors to gene expression using Gaus...

Nicolò Fusi

May 03, 2010

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Lecture
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21:13

Using sequential Monte Carlo approaches as a design tool in synthetic biology

Chris Barnes

May 03, 2010

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Lecture
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24:33

Decoding underlying behaviour from destructive time series experiments through G...

Antti Honkela

May 03, 2010

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2923 Views

Lecture
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15:13

Identifying interactions in the time and frequency domains in local and global n...

Cunlu Zou

May 03, 2010

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3452 Views

Lecture
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12:28

Deterministic and stochastic models of bicoid protein gradient formation in Dros...

Wei Liu

May 03, 2010

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3682 Views

Lecture
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22:40

Statistical analysis of protein patternation on cell membranes during immunologi...

Vladimir Miloserdov

May 06, 2010

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2624 Views

Lecture
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26:54

Machine learning methods for effective proteomics image analysis

Elias S. Manolakos

May 03, 2010

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3891 Views

Lecture