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EpiAgent, a transformer-based foundation model pretrained on approximately 5 million cells and over 35 billion tokens, has advanced single-cell epigenomics by encoding chromatin accessibility as ‘cell sentences’. Benefiting from this framework, EpiAgent achieved state-of-the-art performance in typical downstream tasks and enabled perturbation response prediction and in silico chromatin region knockouts.
GraphPep presents an interaction-derived and protein language model-powered graph learning framework for robust scoring of protein–peptide complexes, substantially enhancing the binding mode prediction of protein–peptide docking.
Eugene Vasiliev started developing Agama to support both personal research and the growing needs of the stellar and galactic dynamics community. Looking ahead, Agama is set to become an all-rounder for dynamical modelling.
EpiAgent, a transformer-based foundation model pretrained on approximately 5 million cells and over 35 billion tokens, has advanced single-cell epigenomics by encoding chromatin accessibility as ‘cell sentences’. Benefiting from this framework, EpiAgent achieved state-of-the-art performance in typical downstream tasks and enabled perturbation response prediction and in silico chromatin region knockouts.
Tools such as ChatGPT can be used to generate almost-identical research papers that pass standard plagiarism checks. Hundreds are thought to have been published.
