Translational Oncological Research
Computational Biology is defined by WikiPedia as an interdisciplinary field that applies the techniques of computer science, applied mathematics and statistics to address biological problems. My scientific interest lies in applying computational biology and biostatistic approaches in translational oncological research. My work generally targets two questions: MoA analysis of drug targeting and drug resistance, as well as novel prognostic biomarker identification. To thie end, I develop algorithms, design statistical models and implement software to profile human cancer-related signaling transduction and gene regulatory networks. I collaborate very closely with biology experimentalists, bioinformaticians/computer scientists as well as clinicians internal and external of the division.
Reseach topics
- Quantitative cell-based high-throughput screenings (HTS) to profile signaling pathways with oncological relevance
- Genome-wide RNAi screening to identify MAPK pathway modulators (on-going, 3. Milestone reached)
- Sub-genome RNAi screening to identify miR-21 modulators (on-going, 2. Milestone reached)
- Sub-genome RNAi screening to identify miR-31/miR-155 modulators with dual-vector system (on-going, 2. Milestone reached)
- Compound screening to investigate cell cycle regulators (submitted)
- Systematic proteomics screening of ERBB signaling system with human microRNA mimic library by RPPA (submitted)
- miR-200bc/429 family regulating cell proliferation, cell cycle and invasion differetially from miR-200a/141 by targeting PLCG1 [PubMed]
- Real-time screening of cell proliferation upon RNAi perturbation with the RTCA system [PLoS One Free Text]
- Human microRNA mimics library screening to identify NFkB-pathway modulating microRNAs (submitted)
- EGF-dependent cell migration modulator screen of transcript-specific RNAi with high-content microscopy (preparatory)
- Clinical studies and MoA studies
- Multiple-layer analysis and data integration of signal transduction and molecular pathology of GIST in retrospective clinical studies [PubMed]: mRNA, small RNA [PubMed], methylation and proteomics (collaboration with Dr. Florian Haller, Uni-Klinikum Freiburg). [Posterpreisträger 2010]
- Breast cancer: Novel tyrosine kinase inhibitor (TKI) MoA analysis in mouse model and drug resistance mechanism analysis (on-going, 2. Milestone reached, collaboration with Dr. Hynes from FMI Basel/Novartis)
- Ovarian cancer: identify novel receptor types of tumorgenesis ligand witih bioinformatics and functional genomics (submitted).
- Bladder cancer: diagonosis value and functional relevance of novel biomarkers with molecular genomics and pathway analysis (on-going, 2. Milestone reached, AACR 102nd meeting poster, collaboration with LIFE GmbH).
- Data mining of biological pathways and networks in public domains
- KEGGgraph: A graph approach to KEGG PATHWAY in R and Bioconductor. Read paper in Bioinformatics. [PubMed][Bioconductor]
- RpsiXML: Bridging PSI-MI standarized protein-protein interaction data with computational environment R. [Bioconductor]
- ReactomeR, WikiPathwayR: Division-internal data integration tools in R and Bioconductor
- Statistical analysis of quantitative high-throughput cell-based assays
- ddCt: Statistical analysis pipeline of qRT-PCR experiments. [GenomExpress 3.09 (GER)][Bioconductor][application note in Biochemica] (collaboration with Roche Penzberg)
- flowDeconvolutor (Internal): Automatic analysis of DNA-staining cell-cycle experiments with flow cytometry.
- RTCA:
Software toolkit for data import, analysis and visualization of the
real-time cell analyzer (RTCA) system (xCELLigence(R) Roche).[application note in Biochemica].[Bioconductor]
- ScratchIt (Internal): Analysis of would-healing assay (aka. scratch assay) with computer vision tools.
- r-opencv: Interface to computer vision library OpenCV in R.[Project page]
- BioVision: Bioinformatic image and video analysis software suite with r-opencv as backend.
- Identification and functional profiling of biological network motifs
- Network-Analysis-Oriented Computational Biology (NAOCB) platform (on-going, NGFN 2010 Poster/Oral Talk)
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