Modelling the brain on the computer
The human body is a highly complex network. Diseases can be regarded as perturbations of that network. Environmental influences or genetic changes lead to disruptions in the system. If the system cannot adapt, a critical transition occurs and a disease breaks out. To investigate disease mechanisms, our biologists and medical doctors perform experiments and examine patients. This generates a flood of scientific data. To analyse biological systems in detail, we have created the infrastructure to handle large amounts of data and built the computational tools to use and interpret them.
Quality according to international standards
High-quality data form a solid basis for our research. At the LCSB, we put an emphasis on recording, storing and accessing large amounts of data in accordance with recognised international standards. Through our Responsible and Reproducible Research (R3) initiative, we provide solid infrastructure, data processes and handling methods to increase the quality and reproducibility of scientific results. The LCSB also hosts ELIXIR-LU, Luxembourg’s Node in the European ELIXIR network dedicated to managing and safeguarding scientific data. Through ELIXIR-LU, we provide tools and services for other stakeholders in the country, and serve as an international hub for biomedical data.
From data to knowledge
Once the data are handled according to the highest quality standards, it is time to turn them into knowledge. Our scientists develop mathematical and computational approaches for the visualisation and analysis of different types of data. They build what we call “disease maps”. These huge networks represent what we know about each disease, all the processes involved at the cellular and molecular level. This is effectively an enormous subway map: molecules are like the subway stations that are connected with each other through chemical reactions or interaction. Once the network is built, we can study who is connected to whom, who plays a central role and which roads get blocked or altered in a specific disease. Also, we can simulate what would happen when we interfere with the system, for instance by administering a drug. Such virtual clinical trials are an important step in the development of new therapies, as they can help to narrow down potential candidates and hence speed up the process.
At the LCSB we apply such methods to many aspects of brain research. Be it on the molecular, cellular or whole brain level, computational models are at the core of LCSB’s work. The team of Dr. Alex Skupin has built models of the calcium signaling as well as energy production in mitochondria – the powerhouses of the cells. Researchers from the teams of Assistant Prof. Enrico Glaab and Prof. Reinhard Schneider have discovered several new genes implicated in Alzheimer’s disease and epilepsies, respectively. Prof. Antonio del Sol’s team was able to predict which molecular factors need to be changed to convert one cell type into another using computational models. In addition, our computer scientists around Prof. Jorge Goncalvez interact very closely with Prof. Frank Hertel, neurosurgeon at the Centre Hospitalier de Luxembourg, to develop better ways to place and adjust electrodes used for deep brain stimulation in Parkinson’s patients. In an ongoing project funded by the Michael J. Fox foundation LCSB researchers aim apply deep learning approaches to data from Parkinson’s patients to predict the evolution of the disease. These non-exhaustive examples of LCSB’s computational research show that modelling approaches form a central part in many of our research areas and go hand in hand with experimental work.