Stefan Stark,

"Take chances, make mistakes, get messy!" - Ms. Frizzle, Magic School Bus

Research Assistant

E-Mail
starks@get-your-addresses-elsewhere.inf.ethz.ch
Phone
+41 44 632 23 74
Address
ETH Zürich
Department of Computer Science
Biomedical Informatics Group Universitätsstrasse 6
CAB F52.1
8092 Zürich
Room
CAB F52.1

I am a research assistant in the Biomedical Informatics Group and masters student in Computer Science

In 2014 I received my Bachelor’s degree in mathematics from New York University and joined the lab shortly after while it was located at Memorial Sloan Kettering Cancer Center in New York City.

I am interested in scaling probabilistic models to clinical data sets. I also contribute to the cancer genomics efforts TCGA PanCanAtlas and ICGC Pan-Cancer Analysis Group.

Abstract Our comprehensive analysis of alternative splicing across 32 The Cancer Genome Atlas cancer types from 8,705 patients detects alternative splicing events and tumor variants by reanalyzing RNA and whole-exome sequencing data. Tumors have up to 30% more alternative splicing events than normal samples. Association analysis of somatic variants with alternative splicing events confirmed known trans associations with variants in SF3B1 and U2AF1 and identified additional trans-acting variants (e.g., TADA1, PPP2R1A). Many tumors have thousands of alternative splicing events not detectable in normal samples; on average, we identified ≈930 exon-exon junctions (“neojunctions”) in tumors not typically found in GTEx normals. From Clinical Proteomic Tumor Analysis Consortium data available for breast and ovarian tumor samples, we confirmed ≈1.7 neojunction- and ≈0.6 single nucleotide variant-derived peptides per tumor sample that are also predicted major histocompatibility complex-I binders (“putative neoantigens”).

Authors Andre Kahles, Kjong-Van Lehmann, Nora C. Toussaint, Matthias Hüser, Stefan Stark, Timo Sachsenberg, Oliver Stegle, Oliver Kohlbacher, Chris Sander, Gunnar Rätsch, The Cancer Genome Atlas Research Network

Submitted Cancer Cell

Link DOI

Authors Julia Vogt, Marius Kloft, Stefan Stark, S S Raman, S Prabhakaran, V Roth, Gunnar Rätsch

Submitted Machine Learning

Link DOI