Genetoberfest 2023

Events |

Crossing the bridges between bioinformatics and clinical research.

Date October 16 to 19, 2023
Location TUM-IAS, TUM Campus Garching, Technical University of Munich
Website exbio.wzw.tum.de/genetoberfest2023/

With this conference we want to cross the bridges between theory and clinical practice, hence, find common ground between bioinformaticians and clinicians.

At this conference, we offer 2 keynote talks and 13 plenary talks, and 1 wrap-up talk by undergraduate students separated into seven sessions by invited people. We further urge the community to submit abstracts for the 24 flash talks and two poster sessions.

Session descriptions:

Discovery of gene-regulatory (network) Mechanisms

Gene regulatory networks encompass a multitude of regulatory layers ranging from transcription factors to long non-coding RNAs, circRNAs or microRNAs. Furthermore, epigenetic mechanisms, such as DNA methylation or histone modifications, are key determinants of gene activity. This session will focus on current challenges and advances in the discovery and understanding of gene regulatory mechanisms and networks.

Using AI in Genetic diagnostics

Artificial intelligence (AI) has shown impressive results across fields and is starting to gain traction in the medical domain, especially in image processing. However, the expected breakthrough in genetics has not yet materialized despite countless genome-wide association studies. Considering the potential of AI in genetic diagnostics, this session will focus on current challenges and future developments.

Implementing OMICS technology in Clinical Practice

OMICS technologies (e.g., genomics, transcriptomics, proteomics, and metabolomics) allow an understanding of the molecular landscapes in an unprecedented resolution. Even though OMICS technologies have shown potential for prognosis, diagnostics, and treatment monitoring, their use in clinical routine is still an exception. This session will highlight the successes of OMICS data in clinical practice and discuss how integrating different technologies can lead to more widespread and robust applications.

Data storage and sharing - between FAIR open science and the GDPR and ethics

The unprecedented wealth of biological and genomic data that has already been generated will be dwarfed by the OMICS data that will soon be routinely collected in clinical medicine. In spite of the huge potential of such data for research, we experience that the General Data Protection Regulation and other legislative barriers prevent researchers from leveraging such data towards improving our understanding of diseases and the development of new diagnostic tools. This session will provide an opportunity for discussing FAIR data sharing and usage of valuable datasets for scientific purposes in a GDPR-compliant fashion, to pave the way to open science.

Drug Target Prediction and Drug Repurposing

Eroom’s law shows that the costs for drug discovery have become prohibitively large such that alternative strategies are needed for widening the existing treatment options. Research highlights two avenues here. A better understanding of drug-target interactions will help develop more targeted therapies following the precision medicine paradigm. At the same time, a better understanding of disease mechanisms and drug-target interactions enables informed drug repurposing strategies, where existing drugs can be leveraged effectively and after shortened clinical trials for the benefit of the patients. For both strategies, the availability of high-quality data sets and the successful use of AI methods are imperative. This session is dedicated to assessing current advances in the fields of drug target predictions and drug repurposing.

Latest developments in OMICS technologies

Since the introduction of microarrays in 1995, an ever-increasing variety of new technologies provides new opportunities - among them, single-cell analyses, long-read, and spatial sequencing readouts. With new technologies, new challenges in data analysis arise and more advanced computational methods are needed to unearth the wealth of information from existing data sets. This session will address the latest (sequencing) technological and methodological developments and their impact on clinical diagnostics.