Martin Luther University Halle-Wittenberg

Dr. Jan Grau

Contact

Jan Grau
Institut für Informatik
Martin-Luther-Universität Halle-Wittenberg

room 3.12
Von-Seckendorff-Platz 1
06120 Halle

phone: +49-345-55-24768
fax: +49-345-55-27039

postal address:
Jan Grau
Institut für Informatik
Martin-Luther-Universität Halle-Wittenberg
06099 Halle

Scientific profiles

Tag cloud of paper abstracts until 2015

Tag cloud of paper abstracts until 2015

Overview

Teaching

summer semester 2020

summer semester 2019

winter semester 2018/2019

summer semester 2018

winter semester 2017/2018

summer semester 2017

winter semester 2016/2017

summer semester 2016

winter semester 2015/2016

summer semester 2015

winter semester 2014/2015

summer semester 2014

winter semester 2013/2014

summer semester 2013

winter semester 2012/2013

summer semester 2011

summer semester 2010

winter semester 2009/2010

summer semester 2009

winter semester 2008/2009

Previous semesters

Applications and libraries

Scientific focus

  • computational and statistical analysis of transcription activator-like effectors (TALEs) and their target genes (DFG project)
  • prediction of TALE nuclease off-targets
  • discriminative models for predicting transcription factor binding sites and splice sites
  • discriminative approaches for de-novo discovery of binding motifs and cis-regulatory modules
  • dependencies in DNA-binding sites
  • analysis of ChIP-seq/-exo and protein-binding microarray data
  • prediction of nucleosome positioning
  • prediction of miRNA targets

Publications

Irad E. Ben-Gal, Ayala Shani, Andre Gohr, Jan Grau, S. Arviv, Armin Shmilovici, Stefan Posch, Ivo Grosse: Identification of transcription factor binding sites with variable-order Bayesian networks. Bioinformatics 21(11): 2657-2666 (2005)

Jan Grau, Irad E. Ben-Gal, Stefan Posch, Ivo Grosse: VOMBAT: prediction of transcription factor binding sites using variable order Bayesian trees. Nucleic Acids Research 34(Web-Server-Issue): 529-533 (2006)

Stefan Posch, Jan Grau, Andre Gohr, Irad E. Ben-Gal, Alexander E. Kel, Ivo Grosse: Recognition of cis-Regulatory Elements with Vombat. J. Bioinformatics and Computational Biology 5(2b): 561-577 (2007)

Jens Keilwagen, Jan Grau, Stefan Posch, Ivo Grosse: Recognition of splice sites using maximum conditional likelihood. LWA 2007: 67-72

Jan Grau, Jens Keilwagen, Ivo Grosse, Stefan Posch: On the relevance of model orders to discriminative learning of Markov models. LWA 2007: 61-66

Jan Grau, Jens Keilwagen, Alexander E. Kel, Ivo Grosse, Stefan Posch: Supervised Posteriors for DNA-motif Classification. German Conference on Bioinformatics 2007: 123-134

Patrick Römer, Tina Strauss, Simone Hahn, Heidi Scholze, Robert Morbitzer, Jan Grau, Ulla Bonas, and Thomas Lahaye: Recognition of AvrBs3-Like Proteins Is Mediated by Specific Binding to Promoters of Matching Pepper Bs3Alleles. Plant Physiology: 150(4):1697-1712 (2009)

Jens Keilwagen, Jan Grau, Stefan Posch, and Ivo Grosse: Apples and oranges: avoiding different priors in Bayesian DNA sequence analysis.BMC Bioinformatics: 11(1):149 (2010)

Jens Keilwagen, Jan Grau, Stefan Posch, Marc Strickert, and Ivo Grosse: Unifying generative and discriminative learning principles. BMC Bioinformatics: 11(1):98 (2010)

Stefan Posch, Jan Grau, André Gohr, Jens Keilwagen and Ivo Grosse: Probabilistic approaches to transcription factor binding site prediction. In I. Ladunga, editor,Computational Biology of Transcription Factor Binding, Methods in Molecular Biology. Humana Press: 674:97 (2010)

Jan Grau: Discriminative Bayesian principles for predicting sequence signals of gene regulation. PhD thesis, Martin Luther University Halle–Wittenberg, April 2010.

Jan Grau, Daniel Arend, Ivo Grosse, Artemis G. Hatzigeorgiou, Jens Keilwagen, Manolis Maragkakis, Claus Weinholdt, and Stefan Posch: Predicting miRNA targets utilizing an extended profile HMM. In D. Schomburg and A. Grote, editors, German Conference on Bioinformatics, volume P-173 of Lecture Notes in Informatics (LNI) - Proceedings, pages 81–91, Bonn (2010)

Jens Keilwagen, Jan Grau, Ivan A Paponov, Stefan Posch, Marc Strickert, and Ivo Grosse: De-novo discovery of differentially abundant transcription factor binding sites including their positional preference. PLoS Computational Biology, 7(2):e1001070 (2011)

Jan Grau, Jens Keilwagen, André Gohr, Berit Haldemann, Stefan Posch, and Ivo Grosse: Jstacs: A java framework for statistical analysis and classification of biological sequences.Journal of Machine Learning Research, 13(Jun):1967–1971, (2012)

Jan Grau, Annett Wolf, Maik Reschke, Ulla Bonas, Stefan Posch, and Jens Boch: Computational predictions provide insights into the biology of TAL effector target sites. PLoS Comput Biol, 9(3):e1002962, 03 2013.

Jan Grau, Jens Keilwagen, André Gohr, Ivan A. Paponov, Stefan Posch, Michael Seifert, Marc Strickert, and Ivo Grosse: Dispom: A discriminative de-novo motif discovery tool based on the Jstacs library. Journal of Bioinformatics and Computational Biology, 11(1), 2013.

Jan Grau, Jens Boch, and Stefan Posch: TALENoffer: genome-wide TALEN off-target prediction. Bioinformatics, 29(22):2931–2932, 2013.

Jan Grau, Stefan Posch, Ivo Grosse, and Jens Keilwagen: A general approach for discriminative de novo motif discovery from high-throughput data. Nucleic Acids Research, 41(21):e197, 2013.

Annekatrin Richter, Jana Streubel, Christina Blücher, Boris Szurek, Maik Reschke, Jan Grau, and Jens Boch: A TAL effector repeat architecture for frameshift binding. Nature Communications, 5, 2014.

Jens Keilwagen, Ivo Grosse, and Jan Grau: Area under precision-recall curves for weighted and unweighted data. PLoS ONE, 9(3):e92209, 2014.

Jan Grau, Ivo Grosse, and Jens Keilwagen. PRROC: computing and visualizing precision-recall and receiver operating characteristic curves in R. doi:10.1093/bioinformatics/btv153   . Bioinformatics, 2015.

J. Keilwagen and J. Grau. Varying levels of complexity in transcription factor binding motifs. doi:10.1093/nar/gkv577    Nucleic Acids Research, 2015.

Oliver A Müller, Jan Grau, Sabine Thieme, Heike Prochaska, Norman Adlung, Anika Sorgatz, and Ulla Bonas. Genome-Wide Identification and Validation of Reference Genes in Infected Tomato Leaves for Quantitative RT-PCR Analyses. PLOS ONE 10(8):E0136499, 2015.

Jan Grau, Ivo Grosse, Stefan Posch, Jens Keilwagen. Motif clustering with implications for transcription factor interactions. doi:10.7287/peerj.preprints.1302v1   . German Conference on Bioinformatics 2015, University Alliance Ruhr, Dortmund, 2015.

Martin Nettling, Hendrik Treutler, Jan Grau, Jens Keilwagen, Stefan Posch, and Ivo Grosse. DiffLogo: a comparative visualization of sequence motifs. BMC Bioinformatics 16(387), 2015.

Jan Grau, Maik Reschke, Annett Erkes, Jana Streubel, Richard D. Morgan, Geoffrey G. Wilson, Ralf Koebnik, and Jens Boch. AnnoTALE: bioinformatics tools for identification, annotation, and nomenclature of tales from Xanthomonas genomic sequences. Scientific Reports 6 21077, 2016.

Jens Keilwagen, Michael Wenk, Jessica L. Erickson, Martin H. Schattat, Jan Grau, and Frank Hartung. Using intron position conservation for homology-based gene prediction. Nucleic Acids Research, 2016.

Jana Trenner, Yvonne Poeschl, Jan Grau, Andreas Gogol-Döring, Marcel Quint, and Carolin Delker. Auxin-induced expression divergence between Arabidopsis species may originate within the TIR1/AFB–AUX/IAA–ARF module. Journal of Experimental Botany, erw457, 2016.

Ralf Eggeling, Ivo Grosse, and Jan Grau. InMoDe: tools for learning and visualizing intra-motif dependencies of DNA binding sites. Bioinformatics, btw689, 2016.

Jana Streubel, Heidi Baum, Jan Grau, Johannes Stuttmann, and Jens Boch. Dissection of TALE-dependent gene activation reveals that they induce transcription cooperatively and in both orientations. PLOS ONE, 12(3):e0173580, 2017.

Annett Erkes, Maik Reschke, Jens Boch, and Jan Grau. Evolution of transcription activator-like effectors in Xanthomonas oryzae. Genome Biology and Evolution, evx108, 2017.

Heike Prochaska, Sabine Thieme, Sebastian Daum, Jan Grau, Cornelius Schmidtke, Magnus Hallensleben, Peter John, Kirsten Bacia, and Ulla Bonas. A conserved motif promotes HpaB‐regulated export of type III effectors from Xanthomonas. Molecular plant pathology, 19(11):2473-2487, 2018. doi:10.1111/mpp.12725   

Jens Keilwagen, Frank Hartung, Michael Paulini, Sven O Twardziok, and Jan Grau. Combining RNA-seq data and homology-based gene prediction for plants, animals and fungi. BMC Bioinformatics, 19:189, 2018. doi:10.1186/s12859-018-2203-5   

Stefanie Mücke, Maik Reschke, Annett Erkes, Claudia-Alice Schwietzer, Sebastian Becker, Jana Streubel, Richard D Morgan, Geoffrey G Wilson, Jan Grau, and Jens Boch. Transcriptional reprogramming of rice cells by Xanthomonas oryzae TALEs. Frontiers in Plant Science, 2019. doi:10.3389/fpls.2019.00162   

Jens Keilwagen, Frank Hartung, and Jan Grau. GeMoMa: Homology-Based Gene Prediction Utilizing Intron Position Conservation and RNA-seq Data in Gene Prediction, Humana, New York, 161-177, 2019. doi:10.1007/978-1-4939-9173-0_9

Marco Cavalli, Nicholas Baltzer, Husen M Umer, Jan Grau, Ioana Lemnian, Gang Pan, Ola Wallerman, Rapolas Spalinskas, Pelin Sahlén, Ivo Grosse, Jan Komorowski, and Claes Wadelius. Allele specific chromatin signals, 3D interactions, and motif predictions for immune and B cell related diseases. Scientific Reports 9:2695, 2019. doi:10.1038/s41598-019-39633-0   

Jan Grau, Stefan Posch, and Jens Keilwagen. Aus Fehlern lernen - Wo binden Transkriptionsfaktoren an die DNA? BIOspektrum, 25(3):346-347, 2019. doi:10.1007/s12268-019-1057-3

Jan Grau, Martin Nettling, and Jens Keilwagen. DepLogo: Visualizing sequence dependencies in R. Bioinformatics 35(22): 4812-4814, 2019. doi:10.1093/bioinformatics/btz507   

Jens Keilwagen, Stefan Posch, and Jan Grau. Accurate prediction of cell type-specific transcription factor binding. Genome Biology 20:9, 2019. doi:10.1186/s13059-018-1614-y   

Giovanna Ambrosini, Ilya Vorontsov, Dmitry Penzar, Romain Groux, Oriol Fornes, Daria D Nikolaeva, Benoit Ballester, Jan Grau, Ivo Grosse, Vsevolod Makeev, Ivan Kulakovskiy, and Philipp Bucher. Insights gained from a comprehensive all-against-all transcription factor binding motif benchmarking study. Genome Biology 21:114, 2020. doi:10.1186/s13059-020-01996-3   

Talks

Accurate prediction of cell type-specific transcription factor binding. German Conference on Bioinformatics 2019, Heidelberg.

Bioinformatics for the Xanthomonas-plant pathosystem. Central German Meeting on Bioinformatics 2018, Mittweida.

Prediction of in-vivo transcription factor binding sites in plants. ECCB 2018, Athens.

Accurate prediction of in-vivo transcription factor binding across cell types. ISMB 2017, Prague.

Bioinformatische Vorhersage gewebespezifischer Genregulation. Lange Nacht der Wissenschaften 2017, Halle.

Accurate prediction of in-vivo transcription factor binding across cell types (keynote). Central German Meeting on Bioinformatics 2017, Leipzig.

AnnoTALE: bioinformatics tools for identification, annotation, and nomenclature of TALEs from Xanthomonas genomic sequences.
German Conference on Bioinformatics 2016, Berlin.

Motif clustering with implications for transcription factor interactions. German Conference on Bioinformatics 2015, Dortmund.

Varying levels of complexity in transcription factor binding motifs (highlight talk). German Conference on Bioinformatics 2015, Dortmund.

Complexity of transcription factor binding motifs. RegGenSIG at ISMB 2015, Dublin.

A general approach for de novo motif discovery from high-throughput data (highlight talk), German Conference on Bioinformatics 2014, Bielefeld

A general approach for de novo motif discovery from high-throughput data, Symposium on Novel Applications of Deep Sequencing in Medicine, Genomics, and Biodiversity Research 2014, Halle

Discriminative de novo motif discovery from high-throughput data (invited), CSC ChIP- and DNase-seq data analysis workshop, 2014, Helsinki, Finnland

Computational prediction of TALEN & CRISPR off-targets (invited), 2014, TALEN & CRISPR TRAINING SCHOOL, Halle

TALEs and Motifs: Bioinformatics with a focus on sequence analysis (invited), 2014, Institute of Plant Biochemistry, Halle

The Jstacs library and its application to de-novo motif discovery (invited), 2013, JCB Workshop “Bioinformatics meets Biodiversity”, Jena

TALEs of virulence and biotechnology (highlight talk), German Conference on Bioinformatics 2013, Göttingen

Computational prediction of TAL effector target sites, 2013, Meeting on Gene Regulation and Information Theory, Halle

Neue Einblicke in die Biologie von TAL-Effektor-Zielsequenzen mittels rechnergestützter Vorhersagen (invited), 2013, Julius Kühn institute, Quedlinburg

De-Novo Discovery of Differentially Abundant DNA Binding Sites Including Their Positional Preference (highlight talk), German Conference on Bioinformatics 2011, Weihenstephan

Predicting miRNA targets utilizing an extended profile HMM, German Conference on Bioinformatics 2010, Braunschweig

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