In recent years, the rapid growth of biological data has increased interest in using
bioinformatics to analyze and interpret this data. Proteomics, which studies the structure …

Within drug discovery, the goal of AI scientists and cheminformaticians is to help identify
molecular starting points that will develop into safe and efficacious drugs while reducing …

Abstract Ribosome profiling (Ribo-Seq) has proven transformative for our understanding of
the human genome and proteome by illuminating thousands of noncanonical sites of …

Building a reference set of protein-coding open reading frames (ORFs) has revolutionized
biological process discovery and understanding. Traditionally, gene models have been …

In the decades following the discovery that genes encode proteins, scientists have tried to
exhaustively and comprehensively characterize the human genome. Recent advances in …

Endometrial cancer (EC) with Mismatch Repair deficiency (MMRd) is characterized by the
accumulation of insertions/deletions at microsatellite sites. These mutations lead to the …

Background Neoantigens, mutated tumour-specific antigens, are key targets of anti-tumour
immunity during checkpoint inhibitor (CPI) treatment. Their identification is fundamental to …

The Transformer model precisely predicts soil health status from high-throughput
sequencing data. The SMOTE algorithm addresses data imbalance issues, improving model …

Ribosome profiling (Ribo-seq) has proven transformative for our understanding of the
human genome and proteome by illuminating thousands of non-canonical sites of ribosome …

In recent times, Transformer-based language models are making quite an impact in the field
of natural language processing. As relevant parallels can be drawn between biological …