Workshop

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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 - 09:45 Jan Grau & Jens Keilwagen Tutorial Introduction to Jstacs

Information about: Alphabet, AlphabetContainer, Sequence, Sample, Model, ScoringFunction, Classifier, Optimization, Parameter, ParameterSet, StrandModel

09:45 - 10:00 Break
10:00 - 10:45 Jan Grau & Jens Keilwagen Tutorial New Features of Jstacs 1.5

Information about: Alignment, HMM package, Discriminative Sampling

11:00 - 11:30 Lasse Feldhahn Talk Discriminative Metropolis sampler for motif discovery
11:30 - 13:00 Lunch
13:00 - 13:30 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 generalization of this approach based on the Tsallis entropy and its implementation in Jstacs.

13:30 - 14:00 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.

14:00 - 14:15 Break
14:15 - 14:45 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.

14:45 - 15:15 Martin Gleditzsch Talk PhyloBayes: An approach to model simultaneously evolutionary dependencies and statistical dependencies between neighbored DNA-Positions with Bayesian Networks
15:15- 15:30 Break
15:30 - 16:30 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.