Traditional computational approaches to design chemical species are limited by the need to
compute properties for a vast number of candidates, eg, by discriminative modeling …

Recent progress in engineering highly promising biocatalysts has increasingly involved
machine learning methods. These methods leverage existing experimental and simulation …

Enzyme engineering plays a central role in developing efficient biocatalysts for
biotechnology, biomedicine, and life sciences. Apart from classical rational design and …

Given concerns about the reproducibility of scientific findings, neuroimaging must define
best practices for data analysis, results reporting, and algorithm and data sharing to promote …

With the goal of accelerating the design and discovery of metal–organic frameworks (MOFs)
for electronic, optoelectronic, and energy storage applications, we present a dataset of …

Compilation, curation, digitization, and exploration of the phytochemical space of Indian
medicinal plants can expedite ongoing efforts toward natural product and traditional …

Decades of nanotoxicology research have generated extensive and diverse data sets.
However, data is not equal to information. The question is how to extract critical information …

Exceptional molecules and materials with one or more extraordinary properties are both
technologically valuable and fundamentally interesting, because they often involve new …

Owing to the chemical pluripotency and viscoelastic nature of electronic polymers, polymer
electronics have shown unique advances in many emerging applications such as skin-like …

EukProt is a database of published and publicly available predicted protein sets selected to
represent the breadth of eukaryotic diversity, currently including 993 species from all major …