RESEARCH INTEREST, THESIS TOPIC and JOB OFFER

1) Co-Transcriptional Folding Simulations

Application of our recently published BarMap-QA approach (item 38. in the publication list below) to understand the underlying principles of RNA folding during transcription. A well studied example is the SRP (Signal Recognition Particle) RNA. Effects such as co-transcriptional pausing might be much better understood by appropriate in-silico simulations.

2) Detection of non-coding RNAs

Application of our recently published svhip approach (item 37. in the publication list below) for de-novo detection of (long) non-coding RNAs in diverse species such as insects, nematodes and plants.

3) Synthetic Training Data

To train Machine Learning (ML) approaches the compilation of independent training and test data sets is an essential step. The possibility to generate synthetic data for the training step and keeping the valuable and frequently sparse biological data to train ML models seems to be a promising approach.

4) RNA Design

Applying approaches and design principles (e.g. item 26, 29 and 30 in the publication list below) enabled us to successfully design RNA molecules that perform predefined functions (e.g. 25, 34 and 35). There are many more mechanism in a living cell to understand and regulate.

PUBLICATIONS

https://orcid.org/0000-0002-3311-7745

Submitted

39. Klapproth C, Israel E, Käther K, Reinhardt F, Chen J, Prohaska SJ, Stadler PF, Findeiß S, Telomerase RNA gene duplications drive telomeric repeat diversity and evolution in Andrena bees, Molecular Biology and Evolution, submitted.

2024

38. Kühnl F, Stadler PF, Findeiß S, Assessing the Quality of Cotranscriptional Folding Simulations, Methods in Molecular Biology, 2023, doi: 10.1007/978-1-0716-3519-3_14, pre-print.

2023

37. Klapproth C, Zöztsche S, Kühnl F, Fallmann J, Stadler PF, Findeiß S, Tailored machine learning models for functional RNA detection in genome-wide screens, NAR Genomics and Bioinformatics, 2023, doi: 10.1093/nargab/lqad072 pre-print.

36. Findeiß S, Flamm C, Ponty Y, Rational Design of RiboNucleic Acids (Dagstuhl Seminar 22381), Dagstuhl Reports, 2023, doi: 10.4230/DagRep.12.9.121.

2022

35. Ender A, Stadler PF, Mörl M, Findeiß S, RNA Design Principles for Riboswitches that Regulate RNAse P-Mediated tRNA Processing, Methods in Molecular Biology, 2022, doi: 10.1007/978-1-0716-2421-0_11.

34. Ender A, Grafl N, Kolberg T, Findeiß S, Stadler PF, Mörl M, Synthetic Riboswitches for the Analysis of tRNA Processing by eukaryotic RNase P Enzymes, RNA, 2022, doi: 10.1261/rna.078814.121.

2021

33. Klapproth C, Sen R, Stadler PF, Findeiß S, Fallmann J, Common features in lncRNA annotation and classification: A survey, Non-Coding RNA, 2021, doi:10.3390/ncrna7040077.

32. Ender A, Etzel M, Hammer S, Findeiß S, Stadler PF, Mörl M, Ligand-Dependent tRNA Processing by a Rationally Designed RNaseP Riboswitch, NAR, 2021, doi:10.1093/nar/gkaa1282.

2020

2019

30. Hammer S, Günzel C, Mörl M and Findeiß S, Evolving methods for rational de novo design of functional RNA molecules, 2019, doi:10.1016/j.ymeth.2019.04.022.

2018

29. Findeiß S, Hammer S, Wolfinger MT, Flamm C and Hofacker IL, In silico design of ligand triggered RNA switches, Methods, 2018, doi:10.1016/j.ymeth.2018.04.003.

28. Senoussi A, Lee Tin Wah J, Shimizu Y, Robert J, Jaramillo A, Findeiß S, Axmann I and Estevez-Torres A, Quantitative characterization of translational riboregulators using an in vitro transcription-translation system, ACS Synth Bio, 2018, doi:10.1021/acssynbio.7b00387.

2017

27. Findeiß S, Etzel M, Will S, Mörl M, Stadler PF, Design of Artificial Riboswitches as Biosensors, Sensor, 2017, doi:10.3390/s17091990.

26. Hammer S, Tschiatschek B, Flamm C, Hofacker IL and Findeiß S, RNAblueprint: Flexible multiple target nucleic acid sequence design, Bioinformatics, 2017, doi:10.1093/bioinformatics/btx263.

2016

25. Domin G, Findeiß S, Wachsmuth M, Will S, Stadler PF and Mörl M, Applicability of a computational design approach for synthetic riboswitches, Nucleic Acids Research, 2016, doi:10.1093/nar/gkw1267.

2015

24. Wachsmuth M, Lorenz R, Serfling R, Findeiß S, Stadler PF and Mörl M, Design criteria for synthetic riboswitches acting on transcription, RNA Biology, 2015, doi:10.1080/15476286.2015.1017235.

23. Findeiß S, Wachsmuth M, Mörl M and Stadler PF. Design of Transcription Regulating Riboswitches, Methods in Enzymology, 2015, doi:10.1016/bs.mie.2014.10.029.

2014

22. Amman F, Wolfinger MT, Lorenz R, Hofacker IL, Stadler PF and Findeiß S. TSSAR: TSS Annotation Regime for dRNA-seq data, BMC Bioinformatics, 2014, 15:89.

21. Backofen R, Amman F, Costa F, Findeiß S, Richter AS and Stadler PF. Bioinformatics of Prokaryotic RNAs , RNA Biology, 2014 May 1;11(5):470-483.

2013

20. Doose G, Alexis M, Kirsch R, Findeiß S, Langenberger D, Machne R , Mörl M, Hoffmann S and Stadler PF. Mapping the RNA-Seq trash bin: Unusual transcripts in prokaryotic transcriptome sequencing data, RNA Biol. 2013 May 13;10(7).

19. Müller SA, Findeiß S, Pernitzsch SR, Wissenbache DK, Stadler PF, Hofacker IL, von Bergen M, Kalkhof S. Identification of new protein coding sequences and signal peptidase cleavage sites of Helicobacter pylori strain 26695 by proteogenomics, J Proteomics. 2013 Jun 28;86:27-42.

18. Wachsmuth M, Findeiß S, Weissheimer N, Stadler PF, Mörl M. De novo design of a synthetic riboswitch that regulates transcription termination. Nucleic Acids Res. 2013 Feb 1;41(4):2541-51.

2012

17. Schmidtke C, Findeiß S , Sharma CM, Kuhfuß J, Hoffmann S, Vogel J, Stadler PF, Bonas U. Genome-wide transcriptome analysis of the plant pathogen Xanthomonas identifies sRNAs with putative virulence functions. Nucleic Acids Res. 2012 Mar;40(5):2020-31.

2011

16. Findeiß S, Engelhardt J, Prohaska SJ, Stadler PF. Protein-coding structured RNAs: A computational survey of conserved RNA secondary structures overlapping coding regions in drosophilids. Biochimie. 2011 Nov;93(11):2019-23.

15. Washietl S, Findeiß S, Müller SA, Kalkhof S, von Bergen M, Hofacker IL, Stadler PF, Goldman N. RNAcode: robust discrimination of coding and noncoding regions in comparative sequence data. RNA. 2011 Apr;17(4):578-94.

14. Lechner M, Findeiß S, Steiner L, Marz M, Stadler PF, Prohaska SJ. Proteinortho: detection of (co-)orthologs in large-scale analysis. BMC Bioinformatics. 2011 Apr;28;12:124.

13. Findeiß S, Langenberger D, Stadler PF and Hoffmann S. Traces of Post-Transcriptional RNA Modifications in Deep Sequencing Data. Biol. Chem., 2011 Apr; 392(4):305-13.

2010

12. Müller SA, Kohajda T, Findeiß S, Stadler PF, Washietl S, Kellis M, von Bergen M and Kalkhof S. Optimization of Parameters for Coverage of Low Molecular Weight Proteins. Analytical and Bioanalytical Chemistry, 2010 Dec; 398(7-8):2867-81

11. Schilling D, Findeiß S, Richter AS, Taylor JA, Gerischer U. The small RNA Aar in Acinetobacter baylyi: a putative regulator of amino acid metabolism. Microbiol., 2010 Sep; 192(9):691-702.

10. Sharma CM, Hoffmann S, Darfeuille F, Reignier J, Findeiß S, Sittka A, Chabas S, Reiche K, Hackermüller J, Reinhardt R, Stadler PF, Vogel J. The primary transcriptome of the major human pathogen Helicobacter pylori. Nature, 2010 Mar; 464(7286): 250-5.

9. Donath A, Findeiß S, Hertel J, Marz M, Otto W, Schulz C, Stadler PF, Wirth S. Noncoding RNA. In Evolutionary Genomics and Systems Biology. ed Caetano-Anollés G, Wiley-Blackwell, Hoboken, (2010); 251-293.

8. Findeiß S, Schubert C, Stadler PF, Bonas U. A novel family of plasmid-transferred anti-sense ncRNAs. RNA Biol, 2010 Mar 8;7(2).

7. Gruber AR, Findeiß S, Washietl S, Hofacker IL, Stadler PF. RNAZ 2.0: IMPROVED NONCODING RNA DETECTION. Pac Symp Biocomput, 2010 Jan; 15:69-79.

2009

6. Hiller M, Findeißsi; S, Lein S, Marz M, Nickel C, Rose D, Schulz C, Backofen R, Prohaska SJ, Reuter G and Stadler PF Conserved introns reveal novel transcripts in Drosophila melanogaster. Genome Res, 2009 Jul; 19(7): 1289-300.

2008

5. Sonnleitner E, Sorger-Domenigg T, Madej MJ, Findeiß S, Hackermüller J, Hüttenhofer A, Stadler PF, Bläsi U, Moll I. Detection of small RNAs in Pseudomonas aeruginosa by RNomics and structure-based bioinformatic tools. Microbiology, 2008 Oct; 154(10): 3175-3187.

4. Wobus M, Wandel E, Prohaska SJ, Findeiß, Tschöp K, Aust G. Transcriptional regulation of the human CD97 promoter by Sp1/Sp3 in smooth muscle cells. Gene, 2008 Apr; 413(1-2): 67-75.

2007

3. Rose D, Hackermüller J, Washietl S, Reiche K, Hertel J, Findeiß S, Stadler PF, Prohaska SJ. Computational RNomics of drosophilids. BMC Genomics, 2007 Nov; 8:406.

2. Drosophila 12 Genomes Consortium. Evolution of genes and genomes on the Drosophila phylogeny. Nature 2007, Nov; 450(7167) :203-18.

2006

1. Hertel J, Lindemeyer M, Missal K, Fried C, Tanzer A, Flamm C, Hofacker IL, Stadler PF; Students of Bioinformatics Computer Labs 2004 and 2005. The expansion of the metazoan microRNA repertoire. BMC Genomics, 2006 Feb; 7:25.