Jonas Reeb

TL;DR: The availability of LocTree3 as a public web server is reported, which includes the machine learning-based LocTree2 and improves over it through the addition of homology-based inference.

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: Testing it on a non‐redundant dataset of 41 TMPs and 285 soluble proteins, and applying strict performance measures, TMSEG outperformed the state‐of‐the‐art in the authors' hands and provides an add‐on improvement for any existing method to benefit from.

TL;DR: This work re‐examined the state of the art in transmembrane helix prediction based on a nonredundant dataset with 190 high‐resolution structures and found PolyPhobius and MEMSAT‐SVM outperformed other methods.