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SELECTBIO Conferences Advances in NGS & Big Data

Stephan Ossowski's Biography



Stephan Ossowski, Group Leader, Centre for Genomic Regulation

Stephan Ossowski, Ph.D., heads the Genomic and Epigenomic Variation in Disease group at the Centre for Genomic Regulation in Barcelona. He has a PhD in Computer Science (Max Planck Institute 2010) and his expertise lies in computational genomics and epigenomics, genetic diseases and cancer. The Ossowski lab is interested in the use of next generation sequencing (NGS) methods in the study of rare and common diseases as well as cancer, with direct application to the clinics. Dr. Ossowski has been involved in several large scale sequencing projects in both plants and animals, including the Arabidopsis 1001 genomes project, the ICGC Chronic Lymphocytic Leukemia project and the IHEC/BLUEPRINT human epigenome project. Key publications include the first NGS based whole-genome sequencing (WGS) of a plant genome in 2008, estimation of mutation rates in Arabidopsis using WGS in 2010 and identification of the novel disease gene KLHL3 for hyperkalemia by Exome-seq in 2012. Recently the Ossowski lab has been involved in several studies investigating the applicability of NGS in clinical settings, e.g. Exome-seq based identification of disease and cancer driver genes as well as targeted sequencing of candidate genes in common metabolic diseases like cystic fibrosis and phenylketonuria. In collaboration with hospitals in Barcelona the group is developing NGS analysis software suitable for diagnostic purposes in clinical practice.

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Signatures of Tumor Clonal Evolution Reveal Novel Driver Genes and Networks in Chronic Lymphocytic Leukemia

Thursday, 15 May 2014 at 08:30

Add to Calendar ▼2014-05-15 08:30:002014-05-15 09:30:00Europe/LondonSignatures of Tumor Clonal Evolution Reveal Novel Driver Genes and Networks in Chronic Lymphocytic LeukemiaAdvances in NGS and Big Data in Barcelona, SpainBarcelona, SpainSELECTBIOenquiries@selectbiosciences.com

Tumors evolve over time and accumulate somatic mutations. Acquisition of alterations conferring a selective growth advantage to neoplastic cells over surrounding normal or tumor cells leads to a rapid increase of the mutated clone within the tumor, resulting in tumor heterogeneity. We have developed a statistical model to exploit signatures of tumor clonal evolution, e.g. cancer cell fraction of somatic mutations, for identification of tumor driver genes and networks. Applying our model to 350 cases of chronic lymphocytic leukemia we identified most known as well as several novel CLL driver genes.


Add to Calendar ▼2014-05-14 00:00:002014-05-15 00:00:00Europe/LondonAdvances in NGS and Big DataAdvances in NGS and Big Data in Barcelona, SpainBarcelona, SpainSELECTBIOenquiries@selectbiosciences.com