Fabio Fabris

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.

TL;DR: It is reported that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bioontologies, working together to improve functional annotation, computational function prediction, and the ability to manage big data in the era of large experimental screens.

TL;DR: The main findings are the link between specific types of DNA repair and ageing; ageing-related proteins tend to be highly connected and seem to play a central role in molecular pathways; ageing/longevity is linked with autophagy and apoptosis, nutrient receptor genes, and copper and iron ion transport.

TL;DR: A new algorithm for identifying the most important and most informative feature values in an RF model is proposed, producing a feature ranking that is much more informative to biologists than an alternative, state‐of‐the‐art feature importance measure.

TL;DR: This paper provides an implementation of a co-evolutionary differential evolution (DE) algorithm in C-CUDA for solving min-max problems and demonstrates that the computing time can be reduced and scalability is improved using C- CUDA.