Language models have contributed to breakthroughs in interdisciplinary research, such as
protein design and molecular dynamics understanding. In this study, we reveal that beyond …

Exiting computational models for drug–target binding affinity prediction have much room for
improvement in prediction accuracy, robustness and generalization ability. Most deep …

The recent marriage of materials science and artificial intelligence has created the need to
extract and collate materials information from the tremendous backlog of academic …

The design of new drugs is expensive, laborious, and complicated, and the vast majority of
new drugs fail in clinical trials. Artificial intelligence, machine learning, and big data are tools …

Our ability to perceive the correlation of different substances in the world is one of the key
aspects of human intelligence. The passing of this faculty to artificial intelligence (AI) …

Single-cell technologies have made it possible to profile millions of cells, but for these
resources to be useful they must be easy to query and access. To facilitate interactive and …

The advent of high-throughput technologies has provided researchers with measurements
of thousands of molecular entities and enable the investigation of the internal regulatory …

In molecular biology, it is a general assumption that the ensemble of expressed molecules,
their activities and interactions determine biological function, cellular states and phenotypes …

Background Symptom phrase recognition is essential to improve the use of unstructured
medical consultation corpora for the development of automated question answering …

Despite significant progress in existing methods for predicting drug-target binding affinity,
there is still room for improvement in better utilizing molecular sequences and designing …