News from the group:
CAMDA'17 Conference
22-23 July 2017,
Prague, Czech Republic
(read more)
Outstanding Presentation Prize
for PP Łabaj
at CAMDA'15 (photo)
OeAW APART fellowship
for PP Łabaj

Sequencing Quality Control (SEQC) project,
MAQC Consortium 2011–2014 (read more)
Host–parasite interactions in biocontrol, WWTF grant 2010–2013 (read more)

Power and limitations of RNA-Seq,
FDA SEQC, Nature Biotechnology (read more)
Characterization and improvement of RNA-Seq precision,
Bioinformatics (read more)
Impact of heavy tails in microarray analysis, Bioinformatics (read more)
Novel conserved repeats in sorting signals,
FEBS Journal (read more)
Sound sensation gene,
Nature communications
(read more)
RNA interference in ageing research,
Gerontology (read more)

We are delighted to present a ring lecture and seminar introducing students to Modern Bioinformatics.

Bioinformatics is a particularly heterogeneous discipline. Rather than only presenting basic material in talks, the focus in this course is on different lecturers showcasing exciting areas of research, modern methods, and current challenges in the field. An aim is to share our excitement with students by providing insight into some of the most interesting and relevant research challenges of these times. The course also offers an invaluable opportunity for meeting several of the key Bioinformatics group leaders in Vienna, and to learn about institutes offering research opportunities towards an M. Sc. thesis in Bioinformatics.

Guest lecturers will introduce the areas of their respective research interests. Each lecture will conclude with a recommendation of scientific papers for further reading and discussion in the seminar.

After the initial lecture presentations, a selection of papers and seminar days for presentations will be provided online (below, updates to be announced during the lectures). You need to select your paper through an online system and provide a critical discussion in the January seminar (instructions will be announced in the lectures and will appear below). Plan for 10-15 minutes of presentation and 5 minutes for discussion. If you are not presenting yourself, you are expected to actively participate in the discussion.

Suggested papers and complementary materials

If you have any difficulties obtaining a copy of the manuscripts from the journal web-page or the below links, please contact us.

David Kreil – Quantitative and functional genomics

  1. An unbiased comparison of hybridization and sequencing based platforms for expression profiling that can discriminate alternative transcripts and spliceforms from the US National Institutes of Health in Bethesda
    Raghavachari et al. (2012) A systematic comparison and evaluation of high density exon arrays and RNA-seq technology used to unravel the peripheral blood transcriptome of sickle cell disease. BMC Medical Genomics, 5, 28.
    For additional background, see our recent paper in Nature Biotechnology, A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium.
  2. An integrated (and controversial?) analysis combining measurements across multiple species from the lab of Ziv Bar-Joseph at Carnegie Mellon University
    Lu et al. (2007) Combined analysis reveals a core set of cycling genes. Genome Biology 8, R146.
If you are interested in in learning about our research interests, please browse our web-site or look at a compilation of typical research projects where you could get involved (contact us for updates).
If you want to take part in an exciting international data analysis challenge, have a look at CAMDA and sign up to the announcements mailing list and check out the contest data sets. In 2017, CAMDA has become a full regular conference track of ISMB, the largest international bioinformatics conference.

Peter Sykacek – Probabilistic Methods in Bioinformatics

  1. R. Verhaak et al. (2010) An integrated genomic analysis identifies subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR and NF1. Cancer Cell 17(1): 98.
  2. M. Hawrylycz et al. (2012) An anatomically comprehensive atlas of the adult human brain transcriptome. Nature 489, 391-399
  3. Victor Pankratius et al. (2016) Computer-Aided Discovery: Toward Scientific Insight Generation with Machine Support, IEEE Intell. Syst. 31, 3-10.
Lecture notes (last updated 2016)

Thomas Rattei – Microbial Metagenomics

  1. Stilianos Louca et al. (2016) Decoupling function and taxonomy in the global ocean microbiome , Science 353, 1272-1277.
  2. Simon Roux et al. (2016) Ecogenomics and potential biogeochemical impacts of globally abundant ocean viruses, Nature 537, 689–693.
Lecture notes (last updated 2015)

Christoph Flamm – Metabolic Network Analysis

  1. Maciek R. Antoniewicz et al. (2007) Elementary metabolite units (EMU): A novel framework for modeling isotopic distributions, Metabolic Engineering 9, 68-86.
  2. Sebastian A. Wahl et al. (2008) 3C labeling experiments at metabolic nonstationary conditions: An exploratory study, BMC Bioinformatics 9, 152.
Lecture notes (last updated 2016)

Chris Oostenbrink – Molecular dynamics simulations

  1. Christian Margreitter and Chris Oostenbrink (2016) Optimization of Protein Backbone Dihedral Angles by Means of Hamiltonian Reweighting, J. Chem. Inf. Model. 56, 1823–1834.
  2. Lingle Wang et al. (2015) Accurate and Reliable Prediction of Relative Ligand Binding Potency in Prospective Drug Discovery by Way of a Modern Free-Energy Calculation Protocol and Force Field, J. Am. Chem. Soc. 137, 2695–2703.
Lecture notes (last updated 2013)

Arndt Haeseler – A Short Introduction To Likelihood in Phylogenetics

  1. Ziheng Yang and Bruce Rannala (2012) Molecular phylogenetics: principles and practice . Nature Reviews Genetics 13, 303-314.
  2. Michael J. Sanderson and H. Bradley Shaffer (2002) Troubleshooting molecular phylogenetic analyses. Annu. Rev. Ecol. Syst. 33, 49–72.
Lecture notes (last updated 2013)

Friedrich Leisch – Clustering, Mixtures and Reproducability of Results

  1. Torsten Hothorn and Friedrich Leisch (2011) Case studies in reproducibility. Brief Bioinform 12 (3), 288-300.
  2. Reanalysis of the results reported in Moyses Nascimento et al., Bayesian model-based clustering of temporal gene expression using autoregressive panel data approach. Bioinformatics, 2012. For R-code of the analysis see the link in the Abstract.
  3. Or reanalysis of the results reported in Riccardo De Bin and Davide Risso A novel approach to the clustering of microarray data via nonparametric density estimation. BMC Bioinformatics, 2011.
Lecture notes (last updated 2015)

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