GoingToMeet

The aim of this workshop is to contribute to the cross-fertilization between the research in machine learning methods and their applications to complex biological and medical questions by bringing together method developers and experimentalists. We encourage submissions bringing forward methods for discovering complex structures (e.g. interaction networks, molecule structures) and methods supporting genome-wide data analysis.

A non-exhaustive list of topics suitable for this workshop:

Methods

Machine Learning Algorithms
Bayesian Methods
Data integration/fusion
Feature/subspace selection
Clustering
Biclustering/association rules
Kernel Methods
Probabilistic Inference
Structured output prediction
Systems identification
Graph inference, completion, smoothing
Semi-supervised learning

Applications

Sequence Annotation
Gene Expression and post-transc

List of Topics. . .