Towards a more inductive world for drug repurposing approaches
Drug–target interaction (DTI) prediction is a challenging albeit essential task in drug repurposing. Learning on graph models has drawn special a…
Drug–target interaction (DTI) prediction is a challenging albeit essential task in drug repurposing. Learning on graph models has drawn special a…
Optimizing the chemical structure of promising drug candidates through systematic modifications to improve potency and physiochemical properties is…
The global data sphere is expanding exponentially, projected to hit 180 zettabytes by 2025, whereas current technologies are not anticipated to s…
Large language models (LLMs) are a form of artificial intelligence system encapsulating vast knowledge in the form of natural language. These syste…
In single-cell sequencing analysis, several computational methods have been developed to map the cellular state space, but little has been done to …
How complex phenotypes emerge from intricate gene expression patterns is a fundamental question in biology. Integrating high-content genotyping app…
Structural variations (SVs) are diverse forms of genetic alterations and drive a wide range of human diseases. Accurately genotyping SVs, particula…
Molecular design using data-driven generative models has emerged as a promising technology, impacting various fields such as drug discovery and the…