EXPANSION: a webserver to explore the functional consequences of protein-coding alternative splice variants in cancer genomics.

Summary: EXPANSION (https://expansion.bioinfolab.sns.

GPCRome-wide analysis of G-protein-coupling diversity using a computational biology approach.

GPCRs are master regulators of cell signaling by transducing extracellular stimuli into the cell via selective coupling to intracellular G-proteins. Here we present a computational analysis of the structural determinants of G-protein-coupling repertoire of experimental and predicted 3D GPCR-G-protein complexes. Interface contact analysis recapitulates structural hallmarks associated with G-protein-coupling specificity, including TM5, TM6 and ICLs.

PRECOGx: exploring GPCR signaling mechanisms with deep protein representations.

In this study we show that protein language models can encode structural and functional information of GPCR sequences that can be used to predict their signaling and functional repertoire. We used the ESM1b protein embeddings as features and the binding information known from publicly available studies to develop PRECOGx, a machine learning predictor to explore GPCR interactions with G protein and β-arrestin, which we made available through a new webserver (https://precogx.bioinfolab.

On the unranked topology of maximally probable ranked gene tree topologies.

A ranked tree topology is a tree topology with a temporal ordering of its coalescence events. Under the multispecies coalescent model, we consider ranked gene tree topologies realized along the branches of ranked species trees, where one gene copy is sampled for each species. Previous results have demonstrated that for almost all ranked species tree topologies with at least five species, there exists a set of branch lengths such that the maximally probable ranked gene tree topologies-those generated with the highest probability under the model-do not match the species tree ranked topology.