Colloquium Computer Science, Alexander Schulz and Markus Lux (Bielefeld University)

Title: Clustering of DNA sequences (ca 20 min. + discussion)

                           

Abstract:

Novel sequencing technologies allow for the analysis of large
amounts of genomic information. Especially, the de novo analysis of
unknown species plays an increasingly important role. Here, analysis
cannot rely on existing information such as from data bases.
Instead, the complex data sets require for unsupervised techniques
such as dimension reduction and clustering. Especially, the latter
plays a particular role, for example in the discovery of new life
forms or the study of the human microbiome. We give an overview on
the problem and show how unsupervised machine learning techniques,
especially clustering, can be used to enable the analysis of this
high-dimensional and potentially noisy data.

Colloquium coordinators are Prof.dr. M. Aiello (e-mail : M.Aiello rug.nl ) and
Prof.dr. M. Biehl (e-mail: M.Biehl rug.nl )

http://www.rug.nl/research/jbi/news/colloquia/computerscience

Title: Visualization of Classifiers (ca. 20 min. + discussion)

                           

Abstract:

Albeit automated classifiers offer a standard tool in many application areas, there exists hardly a generic possibility to directly inspect their behavior. We present a framework how to visualize a given classifier and its behavior as concerns a given data set in two dimensions. More specifically, we use modern nonlinear dimensionality reduction (DR) techniques to project a given set of data points and their relation to the classification decision boundaries. With a given data set, this framework can be used to visualize any trained classifier which provides a probability or certainty of the classification together with the predicted class label.

Colloquium coordinators are Prof.dr. M. Aiello (e-mail : M.Aiello rug.nl ) and
Prof.dr. M. Biehl (e-mail: M.Biehl rug.nl )

http://www.rug.nl/research/jbi/news/colloquia/computerscience