Bioinformatics
Welcome to the website of the Professorship of Bioinformatics at TUM Campus Straubing for Biotechnology and Sustainability led by Prof. Dr. Dominik Grimm.
The research lab conducts research in the field of bioinformatics and machine learning, focusing on the development of statistical and machine learning methods to better understand complex biological systems, their functioning and biochemical properties. For this purpose, the lab works on methods to detect genotype-phenotype relationships and to extract phenotypic features from imaging data. These methods have applications in genetics, precision medicine, and precision agriculture. An emerging area of research is the development of artificial intelligence to solve problems in life sciences and chemistry without including specific prior knowledge.
Lab News
New Article in Nature Methods: Guiding questions to avoid data leakage in biological machine learning applications
Artificial intelligence (AI) has become indispensable in biological research and is driving major advances. However, in certain cases, real-world applications fail to confirm reported predictive performance. One of the main reasons for this is data leakage, i.e. the unauthorized transfer of information between training and test data.
In this Nature Methods Perspective, we present seven questions that should be asked to prevent data leakage when constructing machine learning models in biological domains. By applying these questions to real examples in biology, we aim to make researchers aware of the complex latent interdependencies and possibilities of data leakage in biological applications. We strongly encourage researchers to engage in an interdisciplinary dialogue and to consult domain experts from both domains to ensure robust, reliable, and reproducible ML research in biology.
TMLR Paper awarded with “Featured” certification
Our latest paper “Self-Improvement for Neural Combinatorial Optimization: Sample Without Replacement, but Improvement” has been published in Transactions on Machine Learning Research (TMLR). This is impressive work by Jonathan Pirnay and was awarded with a “Featured” Certification.
Keynote Talk @ ECML, Machine Learning for Chemistry and Chemical Engineering (ML4CCE)
Dominik has given a invited keynote talk at the European Conference on Machine Learning and Data Mining at the Machine Learning for Chemistry and Chemical Engineering (ML4CCE) Workshop about „Automated flowsheet synthesis with deep reinforcement learning“
