In our group we are aiming at a quantitative understanding of biological systems to an extent that one is able to predict systemic features and with the hope to rational design and modify their behaviour. This applies to any system comprising biological components that is more than the mere sum of its components, or, in other words, the addition of the individual components results in systemic properties that could not be predicted by considering the components individually. By achieving this objective we are aiming at new global understanding and treatment of human diseases in which the target will not be a single molecule but a network. For this purpose in our group we develop on one hand new software and theoretical approximations to understand complex systems and on the other we do experiments to validate our predictions.
Protein-assisted RNA fragment docking (RnaX) for modeling RNA–protein interactions using ModelX
Abstract: RNA–protein interactions are crucial for such key biological processes as regulation of transcription, splicing, translation, and gene silencing, among many others. Knowing where an...Read More
Determination of the Gene Regulatory Network of a Genome-Reduced Bacterium Highlights Alternative Regulation Independent of Transcription Factors
Abstract: Here, we determined the relative importance of different transcriptional mechanisms in the genome-reduced bacterium Mycoplasma pneumoniae, by employing an array of experimental techniques under...Read More
The role of clonal communication and heterogeneity in breast cancer
Researchers from our group have collaborated in the recent publication of the work of Dr. Santiago Ramón y Cajal and his group. Abstract: Background Cancer...Read More