Workshop

The first Jstacs workshop will be held on May, 19th at Martin Luther University. The aim of the workshop is to increase the visibility of Jstacs and the implemented projects, to bring developers and users together, as well as to identify further needs.

Depending on the audience the workshop will be held in English or German.

Program

Time	Presenter	Type	Title & Infos
09:00 - 10:00	Jan Grau & Jens Keilwagen	Tutorial	Introduction to Jstacs Information about: Alphabet, AlphabetContainer, Sequence, Sample, Model, ScoringFunction, Classifier, Optimization, Parameter, ParameterSet, StrandModel
10:00 - 10:45	Jan Grau & Jens Keilwagen	Tutorial	New Features of Jstacs 1.5 Information about: Alignment, HMM package, Discriminative Sampling
10:45 - 11:15	Michael Scharfe	Talk	A Hidden Markov Model for Phylogenetic Footprinting Abstract: Phylogenetic footprinting is an important method to discover overrepresented and cross-species conserved sequence motifs (e.g. TFBSs). An extension of the classical Hidden Markov Model that implements phylogenetic emissions was developed using the HMM-Package of the current Jstacs version.
11:15 - 13:00	Lunch
13:00 - 13:30	Michael Seifert	Talk	Exploiting prior knowledge and gene distances in the analysis of tumor expression profiles with extended Hidden Markov Models Abstract: Changes in gene expression levels play a central role in tumors. Additional information about the distribution of gene expression levels and distances between adjacent genes on chromosomes should be integrated into the analysis of tumor expression profiles. We use a Hidden Markov Model with distance-scaled transition matrices (DSHMM) to incorporate chromosomal distances of adjacent genes on chromosomes into the identification of differentially expressed genes in breast cancer.
13:30 - 14:00	Ralf Eggeling	Talk	Maximum Tsallis Entropy Models Abstract: Classifying short sequence signals is a standard task in genome analysis. One important application is to distinguish splice donor and acceptor sites from decoy. A standard solution of the problem utilizes the maximum entropy principle. Here, we discuss a generalizion of this approach based on the Tsallis entropy and its implementation in Jstacs.
14:00 - 14:30	Martin Gleditzsch	Talk	PhyloBayes: An approach to model simultaneously evolutionary dependencies and statistical dependencies between neighbored DNA-Positions with Bayesian Networks
14:30 - 15:15		Discussion	Discussion on future directions and improvements of Jstacs

Location

The workshop will be held on May, 19th in room 5.09 at the Institute of Computer Science at Martin Luther University Halle (Von-Seckendorff-Platz 1).

Contact

If you have any questions or comments, please do not hesitate to contact us by mail jstacs@informatik.uni-halle.de.