Deep Sequencing October 2008 – presented at 1st workshop on high throughput sequencing; ETH Zurich in Basel This poster documents the data layout and primary processing of the data

Modulation of p53 protein isoforms and their function in acute myeloid leukaemia October 2008 – presented at FEBS Meeting Oslo p53 is a highly regulated tumour suppressor protein involved in the proliferative suppression of damaged cells. p53 is mutated in 50% of all cancers, confirming its importance in cancer development.1 In cancer with TP53, mutations of other proteins upstream or downstream of p53 is likely to affect its function. A way to combat these cancers may be to re-establish a functional p53 pathway, thereby killing the malignant cells. The TP53 gene can transcribe ten different p53 isoforms, and we believe that these isoforms have functional differences, and the expression of these is important in p53 response to cell damage.2 p53 is highly regulated through post-translational modifications, such as ubiquitinations, phosphorylation and acetylations.3 As a way to visualize in what degree p53 is modified and what isoforms are expressed, we have chosen to use 2D Western blot.

Deep Sequencing October 2008 – presented at All Systems X day In parallel to the human genome sequencing initiative several new technologies have emerged that allow sequencing at unprecedented throughput and low costs. These approaches are generally referred to as “deep sequencing”. They enable researchers to not only re-sequence genomes and thus to identify genome variations but also to quantify the abundance of experimentally enriched fractions of the genome. The very large numbers of short individual sequence reads produced by the Illumina Genome Analyzer (currently approx. 50 million reads per instrument run) are well suited to make direct quantitative measurements of the sequence content of a DNA sample. By determining a short sequence read from each of many randomly selected molecules from the sample and then mapping each sequence read onto the reference genome, the identity of each starting molecule is learned, and its frequency in the sample can be calculated. Desired levels of sensitivity and statistical certainty, needed to detect rare molecular species, can be achieved by adjusting the total number of sequence reads. Sequence census assays do not require knowing in advance that a sequence is of interest as a promoter, enhancer or RNA-coding domain, as most current microarray designs do. The combination of chromatin immunoprecipitation assays with the subsequent quantitative analysis of the enriched DNA sample by deep sequencing (ChIP-seq) has been proven to be of great value for whole mammalian genome approaches in several high-profile studies published over the last year. At D-BSSE we have established a deep sequencing unit based on Illumina sequencing technology located in the new “Laboratory for Quantitative Genomics”. This poster gives an overview of the sequencing technology and the data analysis pipeline. Furthermore it provides insights into the quality of our functional genomics data recently generated by ChIP-seq and RNA-seq.

Deep Sequencing October 2008 – presented at ETH Zurich Departmental Retreat Bad Zurzach This poster documents the data layout and primary processing of the data

A Whole-genome RNAi Screen identifies Novel Regulators of Notch Signaling in Drosophila Melanogaster October 2008 – presented at ETH Zurich Departmental Retreat Bad Zurzach Undisclosed

Denoising of MALDI-TOF Mass Spectra May 2005 – presented at AOPC2005, The VIIth European Symposium of the Protein Society, section proteomics, interactomics and protein networks, Barcelona MALDI-TOF mass spectrometry is a well known and widely used technique to fingerprint and sequence proteins. However widely used, the signal output of these machines often contain disturbing artefacts such as static tones, linearly up-sweeping tones, exponentially decaying tones and probabilistic pulse trains. Their presence reduces the accuracy of peak localization and might introduce phantom peaks. This further complicates a) automatic selection of peaks, b) makes it impossible to normalize mass spectrograms and c) in general reduces the performance of high throughput proteomics. We present a) a number of specialized algorithms to remove these artefacts, based on wavelets, and b) a number of techniques to automatically assign confidence scores to peaks, based on autocorrelation techniques and machine modelling. The combination of the presented techniques allow for a very accurate and automated sample analysis, which in turn helps in the determination of the sample content. Static tones are sine waves embedded in the signal, which can shift peak locations backward or forward over the mass/charge axis. Up-sweeping tones and decaying tones are sine waves of which the frequency goes linearly up, or exponentially down over the mass/charge axis, resulting in an immediate correlation between the accuracy of a peak-position and its position on the mass/charge axis. Probabilistic pulse trains are small pulses which might occur at specific positions on the mass/charge axis. Depending on the number of shots summed into one measurement different misinterpretations are possible. Either too few shots are taken, resulting in phantom peaks, or too many shots are taken in which the pulses will overrun the actual measurement

Envision Software Package for the Concerted Study of Biological Data January 2005 – presented at NBS 2005 (Poster), Tromso Quite a lot of names for a crappy project, but I guess that to be the style of the involved groups.

Envision Software Package for the Concerted Study of Biological Data November 2004 – presented at at Bioprosp 2004 (poster), Tromso

Automatic Generation of Concurrency Adaptors for Multi Agents March 2003 – presented at the International Conference on Evolvable Systems 2003 (ICES03), Trondheim