Integrative modeling of biomolecular structures 

                                  

Alexander Schug

Forschungszentrum Jülich and University of Duisburg/ Essen, Germany

 

 

Abstract:

On the molecular level, life is orchestrated through an interplay of many biomolecules. To gain any detailed understanding of biomolecular function, one needs to know their structure. Yet the structural characterization of many important biomolecules and their complexes is challenging. Integrative modeling combines data from multiple sources. Both low-resolution experimental information (e.g. SAXS or FRET) or theory-driven approaches can guide such modeling approaches. For the latter, I will highlight how statistical analysis or Machine Learning can take advantage of both abundant databases as for proteins or limited databases as for RNA and still result in high quality structures.