Tatsiana Aneichyk

    Tatsiana is a data scientist with current focus on functional genomics (gene expression), but with diverse experience in several fields. Her undergrad studies were in Applied Mathematics and Informatics, specializing in Theory of Probabilities and Mathematical Statistics. She has MSc in Industrial Logistics (production optimization, routing, simulations) and a PhD in Molecular Oncology (applied bioinformatics group). 

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As bioinformatics scientist she worked in the fields of oncology and neuroscience. Her PhD was focused on analysis of gene expression and clinical data in patients with acute lymphoblastic leukemia during treatment, investigating mechanisms of resistance. As a post-doc she spent few years at Massachusetts General Hospital and Harvard Medical School working with RNA-Seq data from patients and cell lines, where the team was able to uncover a potential molecular mechanism of X-linked Dystonia-Parkinsonism (Aneichyk et al., Cell, 2018). Since 2019 she works as a freelance data scientist working with academic groups and biomedical companies.

Alvaro Sanchez

Alvaro has a diploma in Engineering Physics and a Master's degree in Medical Imaging Physics. He has worked as Senior Software Engineer in several projects related to last-generation medical imaging devices, image analysis and scientific visualization.  Alvaro has vast experience in computer graphics, volume rendering, cloud computing and software architecture.  He has participated as a core developer in several high impact open-source scientific libraries such as VTK, ITK and ParaView.
 

He has also been part of various successful startup companies and currently works as a Principal Engineer at SmartReporting GmbH.

Steffen Heyne

Steffen is an experienced bioinformatics scientist with more than 7 years of experience in sequence analysis, genomics and data analysis. He has expert knowledge in a wide range of sequencing assays like RNA-seq, Chip-seq, WGBS and single cell protocols. He is proficient in R, Python, Bash and Perl and enjoys implementation of prototypes for new analysis strategies, and can also implement efficient software in C++ including multithreading (C++14). 

Currently he is focused on understanding epigenetic foundations of obesity and diabetes. For this purpose he combines chromatin segmentation with differential expression analysis. In his PhD thesis he has developed an efficient algorithm (GraphClust, Heyne et. al, Bioinformatics 2012, presented at ISMB 2012) for large scale clustering of RNA sequences based on their sequence and secondary structure.

Baiba Vilne

Baiba's background includes both experience in experimental biology as well as bioinformatics and computational biology. She started as a biology major, however, during her Master's studies Baiba developed a great interest in bioinformatics and engaged in a database development project, involving the prediction of protein-protein interactions based on correlated mutations in their respective domains, currently part of the DIMA database.

 

During her PhD, Baiba worked between in silico analysis and wet lab experiments, investigating the regulatory networks of hematopoietic stem cells and their niche. She generated a high-throughput transcriptomics data set, followed by computational analysis involving candidate gene prioritization and biological hypothesis generation, which she then validated experimentally both in vitro and in vivo.

 

For the last 4-5 years Baiba mainly focused on integrative systems-level investigations linking genetic and transcriptomic data, both in mice and human in the context of coronary artery disease. Most recently she has also been involved in numerous projects related to microbiome (16S rRNA amplicon sequencing) analyses and machine learning approaches.

Andrea Prunotto

    Andrea is a Theoretical Physicist. He earned a PhD in Biochemistry, sharpening his computational skills to develop and implement mathematical models related to molecular dynamics and protein folding. Later, he moved to System Biology, gathering a large knowledge in next generation sequencing, genome wide association studies, and integrative analysis of clinical data. He worked as a Senior Lab Manager and Senior Biostatistician in various clinical institutions, such as the University Hospital of Canton Vaud (Lausanne, Switzerland) and the Karolinska Institutet (Stockholm, Sweden). With 15 years in the field of computational biology and biochemistry, Andrea is the most experienced scientist at IDL. 

Gregor Sturm

Gregor Sturm is a PhD student at the Institute of Computational Biology at the Medical University of Innsbruck. His current research focuses on leveraging single-cell multi-omics data to study cell-to-cell communication in cancer and chronic inflammatory diseases.

 

Before, he obtained a Bachelor's and Master's degree from the joint Bioinformatics programme of University of Munich and Technical University of Munich. He has more than 10 years of coding experience, is a seasoned software developer and data scientist and is strongly committed to fully reproducible research.

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