Sayoni Das

TL;DR: This article provides an update on the major developments in the 2 years since the last publication in this journal including: significant improvements to the predictive power of the authors' functional families (FunFams); the release of their ‘current’ putative domain assignments (CATH-B); a new, strictly non-redundant data set of CATH domains suitable for homology benchmarking experiments (Cath-40) and a number of improved to the web pages.

TL;DR: Developments to the CATH-Gene3D resource over the last two years since the publication in 2015 are described, including significant increases to the structural and sequence coverage; expansion of the functional families in CATH; building a support vector machine (SVM) to automatically assign domains to superfamilies.

TL;DR: The second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function, was conducted by as mentioned in this paper. But the results of the CAFA2 assessment are limited.

TL;DR: The second critical assessment of functional annotation (CAFA) conducted, a timed challenge to assess computational methods that automatically assign protein function, revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies.

TL;DR: The third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed, concluded that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not.