3rd International Workshop on Machine Learning in Systems Biology (MLSB), Ljubljana 2009

3rd International Workshop on Machine Learning in Systems Biology (MLSB), Ljubljana 2009

20 Videos · Sep 5, 2009

About

Molecular biology and all the biomedical sciences are undergoing a true revolution as a result of the emergence and growing impact of a series of new disciplines/tools sharing the “-omics” suffix in their name. These include in particular genomics, transcriptomics, proteomics and metabolomics, devoted respectively to the examination of the entire systems of genes, transcripts, proteins and metabolites present in a given cell or tissue type.

The availability of these new, highly effective tools for biological exploration is dramatically changing the way one performs research in at least two respects. First, the amount of available experimental data is not a limiting factor any more; on the contrary, there is a plethora of it. Given the research question, the challenge has shifted towards identifying the relevant pieces of information and making sense out of it (a “data mining” issue). Second, rather than focus on components in isolation, we can now try to understand how biological systems behave as a result of the integration and interaction between the individual components that one can now monitor simultaneously (so called “systems biology”).

Taking advantage of this wealth of “genomic” information has become a ‘conditio sine qua non’ for whoever ambitions to remain competitive in molecular biology and in the biomedical sciences in general. Machine learning naturally appears as one of the main drivers of progress in this context, where most of the targets of interest deal with complex structured objects: sequences, 2D and 3D structures or interaction networks. At the same time bioinformatics and systems biology have already induced significant new developments of general interest in machine learning, for example in the context of learning with structured data, graph inference, semi-supervised learning, system identification, and novel combinations of optimization and learning algorithms.

The aim of this workshop is to contribute to the cross-fertilization between the research in machine learning methods and their applications to systems biology (i.e., complex biological and medical questions) by bringing together method developers and experimentalists.

The Workshop is organized as "core - event" of Patterns Analysis, Statistical Modelling and Computational Learning - Network of Excellence 2 (PASCAL 2).


More about the workshop can be found at: http://mlsb09.ijs.si/index.html

Videos

Opening

video-img
06:57

Opening

Sašo Džeroski

Oct 5, 2009

 · 

2721 views

Invited Talks

video-img
57:07

Machine Learning Methods For Protein Analyses

William Stafford Noble

Oct 5, 2009

 · 

3980 views

video-img
49:43

Metadata For Systems Biology

Nick Juty

Oct 5, 2009

 · 

3539 views

video-img
55:34

Automating Science

Ross D. King

Oct 5, 2009

 · 

4699 views

video-img
01:00:13

Synthetic Biology Achievements And Future Prospects

Roman Jerala

Oct 5, 2009

 · 

6737 views

video-img
57:47

Quantitative Microscopy: Bridge Between "Wet" Biology and Computer Science

Yannis L. Kalaidzidis

Oct 5, 2009

 · 

4571 views

video-img
01:02:48

Networking Genes And Drugs: Understanding Gene Function And Drug Mode Of Action ...

Diego di Bernardo

Oct 5, 2009

 · 

4316 views

Session 1: Networks and Function

video-img
22:39

Predicting the Functions of Proteins in PPI Networks from Global Information

Hossein Rahmani

Oct 5, 2009

 · 

3172 views

video-img
23:44

Integrated Network Construction Using Event Based Text Mining

Yvan Saeys

Oct 5, 2009

 · 

3945 views

Session 2: Biomarkers and Disease

video-img
31:15

Evaluation Method For Feature Rankings And Their Aggregations For Biomarker Disc...

Ivica Slavkov

Oct 5, 2009

 · 

3309 views

video-img
19:06

On Utility Of Gene Set Signatures In Gene Expression-Based Class Prediction

Minca Mramor

Oct 5, 2009

 · 

6918 views

Session 3: Development, Signalling

video-img
21:05

Matching Models to Data in Modelling Morphogen Diffusion

Wei Liu

Oct 5, 2009

 · 

4787 views

video-img
23:45

Evaluation Of Signaling Cascades Based On The Weights From Microarray And ChIP-s...

Zerrin Işık

Oct 5, 2009

 · 

3153 views

Session 4: Machine Learning Methodology

video-img
29:16

A Comparison Of AUC-Estimators In Small-Sample Studies

Antti Airola

Oct 5, 2009

 · 

3359 views

video-img
28:54

Accuracy‐Rejection Curves (ARCs) For Comparison Of Classification Methods With R...

Malik Sajjad Ahmed Nadeem

Oct 5, 2009

 · 

3072 views

Session 5: Function Prediction

video-img
37:58

Hierarchical Cost-Sensitive Algorithms For Genome-Wide Gene Function Prediction

Nicolò Cesa-Bianchi

Oct 5, 2009

 · 

2925 views

video-img
23:29

Simple Ensemble Methods Are Competitive With State-Of-The-Art Data Integration M...

Matteo Re

Oct 5, 2009

 · 

3255 views

Session 6: Phenotype Prediction

video-img
27:06

Evaluation Of Methods In Gene Association Studies: Yet Another Case For Bayesia...

Gábor Hullám

Oct 5, 2009

 · 

3940 views

video-img
22:13

A Subgroup Discovery Approach For Relating Chemical Structure And Phenotype Data...

Lan Umek

Oct 5, 2009

 · 

3515 views

Discussion and Closing Remarks

video-img
04:36

Closing Remarks

Sašo Džeroski

Oct 5, 2009

 · 

2604 views