Developments in computational omics technologies have provided new means to access
the hidden diversity of natural products, unearthing new potential for drug discovery. In …

Large language models (LLMs) have emerged as powerful tools in chemistry, significantly
impacting molecule design, property prediction, and synthesis optimization. This review …

Large language models have made significant strides in natural language processing,
enabling innovative applications in molecular science by processing textual representations …

Knowledge in the chemical domain is often disseminated graphically via chemical reaction
schemes. The task of describing chemical transformations is greatly simplified by introducing …

Background Electrocardiogram (ECG) is one of the most common noninvasive diagnostic
tools that can provide useful information regarding a patient's health status. Deep learning …

The number of publications describing chemical structures has increased steadily over the
last decades. However, the majority of published chemical information is currently not …

Molecular structure recognition is the task of translating a molecular image into its graph
structure. Significant variation in drawing styles and conventions exhibited in chemical …

Optical chemical structure recognition from scientific publications is essential for
rediscovering a chemical structure. It is an extremely challenging problem, and current rule …

In the ever-evolving field of drug discovery, the integration of Artificial Intelligence (AI) and
Machine Learning (ML) with cheminformatics has proven to be a powerful combination …

Transformer models have emerged as pivotal tools within the realm of drug discovery,
distinguished by their unique architectural features and exceptional performance in …