Intrinsically disordered proteins (IDPs) are ubiquitously involved in cellular 
processes and often implicated in human pathological conditions. The critical 
biological roles of these proteins, despite not adopting a well-defined fold, 
encouraged structural biologists to revisit their views on the protein 
structure-function paradigm. Unfortunately, investigating the characteristics 
and describing the structural behavior of IDPs is far from trivial, and 
inferring the function(s) of a disordered protein region remains a major 
challenge. Computational methods have proven particularly relevant for studying 
IDPs: on the sequence level their dependence on distinct characteristics 
determined by the local amino acid context makes sequence-based prediction 
algorithms viable and reliable tools for large scale analyses, while on the 
structure level the in silico integration of fundamentally different 
experimental data types is essential to describe the behavior of a flexible 
protein chain. Here, we offer an overview of the latest developments and 
computational techniques that aim to uncover how protein function is connected 
to intrinsic disorder.