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
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Uploaded videos:
Opening
Opening
Oct 05, 2009
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2717 Views
Invited Talks
Networking Genes And Drugs: Understanding Gene Function And Drug Mode Of Action ...
Oct 05, 2009
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4314 Views
Quantitative Microscopy: Bridge Between "Wet" Biology and Computer Science
Oct 05, 2009
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4566 Views
Synthetic Biology Achievements And Future Prospects
Oct 05, 2009
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6731 Views
Machine Learning Methods For Protein Analyses
Oct 05, 2009
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3974 Views
Metadata For Systems Biology
Oct 05, 2009
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3532 Views
Automating Science
Oct 05, 2009
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4689 Views
Session 1: Networks and Function
Predicting the Functions of Proteins in PPI Networks from Global Information
Oct 05, 2009
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3155 Views
Integrated Network Construction Using Event Based Text Mining
Oct 05, 2009
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3943 Views
Session 2: Biomarkers and Disease
On Utility Of Gene Set Signatures In Gene Expression-Based Class Prediction
Oct 05, 2009
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6914 Views
Evaluation Method For Feature Rankings And Their Aggregations For Biomarker Disc...
Oct 05, 2009
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3307 Views
Session 3: Development, Signalling
Matching Models to Data in Modelling Morphogen Diffusion
Oct 05, 2009
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4779 Views
Evaluation Of Signaling Cascades Based On The Weights From Microarray And ChIP-s...
Oct 05, 2009
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3151 Views
Session 4: Machine Learning Methodology
A Comparison Of AUC-Estimators In Small-Sample Studies
Oct 05, 2009
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3356 Views
Accuracy‐Rejection Curves (ARCs) For Comparison Of Classification Methods With R...
Oct 05, 2009
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3069 Views
Session 5: Function Prediction
Hierarchical Cost-Sensitive Algorithms For Genome-Wide Gene Function Prediction
Oct 05, 2009
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2923 Views
Simple Ensemble Methods Are Competitive With State-Of-The-Art Data Integration M...
Oct 05, 2009
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3252 Views
Session 6: Phenotype Prediction
A Subgroup Discovery Approach For Relating Chemical Structure And Phenotype Data...
Oct 05, 2009
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3513 Views
Evaluation Of Methods In Gene Association Studies: Yet Another Case For Bayesia...
Oct 05, 2009
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3938 Views
Discussion and Closing Remarks
Closing Remarks
Oct 05, 2009
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2599 Views