Year: 2025
Type: conference-paper
Abstract: Missense variants alter a single amino acid in proteins and can cause loss-of-function (LOF) or gain-of-function (GOF). Accurately classifying these effects is essential for understanding genetic diseases and tailoring precision medicine approaches. Here, we propose the Gain and Loss of Function Dataset (GLOF), the first dataset of LOF, GOF, and Neutral missense variants annotated by specialists, curated with one of Latin America’s largest genetic diagnostics laboratories. Using embeddings from the ESM-1v model, our Random Forest model achieves state-of-the-art results without requiring complex feature engineering or multi-sequence alignment. We hope the GLOF dataset will stimulate further research into LOF/GOF prediction for personalized genomics.
Authors: Victor Maricato Oliveira, Pedro Nuno de Souza Moura
Institution: Universidade Federal do Estado do Rio de Janeiro
Language: English
Topic: Genomics and Rare Diseases
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
OpenAlex ID: W4410159328