Large-scale analysis and annotation of human genetic data
By Jan Vogel
Lightning talk
Target audience: Advanced
Language: English
Tags: bioinformatics computes discovery drug large research scale science sequencing
The rapid developments of ultra high-troughput sequencing technologies (HTS) within the last years have given us easy access to high quality data sets at decreasing costs; these large-scale genomic data sets are highly valuable for scientists and researchers, as this data can be applied to a wide range of biomedical questions, and it has the potential to greatly accelerate the biological and medical research - with the new drug discoveries and therapies being one of the many results.
With the arrival of these new data types, one current challenge comprises the development of standardized analysis platforms, statistical analyses and robust pipelines to perform complex, reproducible large-scale genomic analyses in a timely manner - this allows scientists to understand the genetic make-up of individual patients and to elucidate the underlying causes of genetic disorders and diseases risks.
In my talk, I will expand on the development of novel bioinformatics tools, workflows and software systems to enable the identification and annotation of genetic differences between different sample types (data from patients, samples and cultured cell lines). My work will lead to efficient algorithms for several difficult optimization problems arising in the processing of genomic on a very large scale, to new methodologies and robust bioinformatics tools to annotate and cross-reference in-house generated data with data in the public domain and to streamlined and optimized workflows.
By enabling scientists and researchers to perform and mine data from large-scale genomic analyses, their work will have far reaching impacts in life sciences, drug discovery, drug development and help patients with serious and live-threatening conditions.
