Works at MDC as of March 2014 as the group leader for the bioinformatics platform. He has experience in computational epigenomics, cancer genomics and regulatory genomics. He is generally interested in large-scale data-sets in biology and machine-learning applications.
Publications: [PubMed] [GoogleScholar] [ImpactStory]
Websites: [LinkedIn] [Mendeley] [Github] [slideshare] [blog]
E-mail: altuna.akalin [at] mdc-berlin [dot] de
Alex is a trained bioinformatician. He is experienced in workflow development and analysis of sequencing data including short/long-read RNA-Seq, ChIP-Seq, ATAC-Seq and BS-Seq.
Publications: [PubMed]
Websites: [LinkedIn] [Github]
E-mail: Alexander.Blume@mdc.berlin.de
Vedran supports research projects for the platform. He has extensive experience in next-generation sequencing analysis: RNA-seq, ChIP-seq, smallRNA-seq and whole genome sequencing.
Publications: [PubMed]
Websites: [LinkedIn] [Github]
E-mail: vedran.franke [at] mdc-berlin [dot] de
Artür is a trained statistician, computational scientist and bioinformatician. His main research interest is Network Science, and he aims to develop graph-based statistical learning frameworks for analyzing omics datasets towards, e.g., Spatial Biology and Biological Knowledge Graphs. He has built several software packages and tools that implement statistical learning methods for knowledge discovery, and he has extensive expertise in analyzing data from a large variety of omics technologies such as scRNA-Seq, CITE-Seq, SLAM-Seq etc..
Publications: [GoogleScholar]
Websites: [Homepage] [LinkedIn] [Github]
E-mail: Artuer.Manukyan@mdc.berlin.de
Dan’s big challenge is to maintain, extend and keep safe the BIMSB’s IT infrastructure consisting of application servers, virtualization systems, storage, databases and dedicated systems used to analyze the biological data. Most of these systems are based on open source technologies (inclusing the operating systems/Linux) and they are designed based on the idea that a scientist must do science and not to loose time with unfriendly IT systems - of course, this cannot be done wihout a very close relationship with the users.
Websites: [LinkedIn]
E-mail: dan.munteanu [at] mdc-berlin [dot] de
Bora has started working at MDC on 1st of August, 2015 as a bioinformatics scientist. He has had a balanced trainining of biological and computational sciences. He is interested in doing large-scale data analysis to understand the molecular biology of diseases. At MDC, he will develop tools and annotation pipelines related to RNA bioinformatics and NGS data analysis, which will be integrated with the Galaxy instance of the Berlin Institute of Medical Systems Biology.
Publications: [PubMed] [GoogleScholar]
Websites: [LinkedIn] [Github] [ResearchGate]
E-mail: bora.uyar [at] mdc-berlin [dot] de
Ricardo provides IT support for BIMSB scientists. He has extensive experience in GNU/Linux system administration (RHCE) and programming.
Since 2014 Ricardo works on GNU Guix, a functional package manager, which allows us to build scientific software reproducibly and manage complex software environments. Ricardo is an Emacs, Scheme, and Free Software enthusiast.
Websites: [Homepage] [Code] [Github]
E-mail: ricardo.wurmus [at] mdc-berlin [dot] de
Enhancing machine learning-aided cancer biology with prior biological knowledge integration.
Publications: [PubMed]
Websites: [LinkedIn] [Github]
E-mail: Taras.Savchyn@mdc.berlin.de
Nour is workin on the development of a genomic patient matching system using tumor genome profiles.
Websites: [LinkedIn] [Github]
E-mail: Nour.Alkhoury@mdc.berlin.de
Jonas started in the lab in April 2022 as a HiWi student working to improve the PiGx-SARS-CoV-2 pipeline’s code quality and deconvolution accurracy. As of September 2022 he is working on his Master’s thesis, exploring the feasibility of improving prediction accurracy of machine learning models using cancer bulk RNA-sequencing through residuals derived from deconvolution models.
2022: Intern, MDC BIMSB, Berlin, Germany
Publications: [PubMed]
Websites: [Github]
E-mail: jonas.freimuth.mdc-berlin.de
Vic-Fabienne acitively participates in a range of projects focused on developing bioinformatics tools for omics science, with a specific emphasis on machine learning. Notably, she have contributed to the PiGx-Sars-Cov-2 analysis pipeline.
Publications: [PubMed]
Websites: [LinkedIn] [Github]
E-mail: Vic-Fabienne.Schumann@mdc.berlin.de
E-mail: sabrina.deter [at] mdc-berlin [dot] de
Visting student in 2022, currently PhD Student at DKFZ
Websites: [LinkedIn]
Visting Researcher in 2022, currently at InstaDeep Ltd
Publications: [GoogleScholar]
Websites: [LinkedIn]
Internship from 2021-2022, currently PhD Student at F.Müller Lab at Saarland University
Publications: [PubMed]
Websites: [LinkedIn]
PhD Student and Bioinformatics Scientist for Arcas.ai from 2015-2022, currently at Inceptive
Publications: [PubMed]
Websites: [LinkedIn]
Postdoctoral Researcher from 2020 - 2022, currently at Eagle Genomics
Publications: [PubMed]
Websites: [LinkedIn]
Bioinformatics Scientist from 2020-2021, currently PhD Student at TU Hamburg
Publications: [PubMed]
Websites: [LinkedIn]
PhD Student from 2015-2021, currently at Ardigen
Publications: [PubMed]
Websites: [LinkedIn]
Bioinformatics Scientist from 2017-2021, currently at Roche Diagnostics
Publications: [PubMed]
Websites: [LinkedIn]
PhD Student from 2015-2019, currently at MDC, Data Management
Websites: [LinkedIn]
Master Thesis in 2020
Websites: [Github]
Bioinformatics Scientist from 2017-2019, currently at Max Planck Institute for Molecular Genetics, Berlin.
Publications:[publications on researchgate]
Websites: [LinkedIn]
Intern in 2017, currently at Ardigen
Websites: [LinkedIn]
Bioinformatics Scientist from 2015-2017, currently at University of Freiburg
Publications: [PubMed]
Webserver: [Web]
E-mail: dilmurat.yusuf [at] gmail [dot] com
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