Artificial intelligence and specifically machine learning applications are nowadays used in a
variety of scientific applications and cutting-edge technologies, where they have a …

Determining the structure of biological macromolecules by X-ray crystallography involves a
series of steps: selection of the target molecule; cloning, expression, purification and …

The preparation of protein single crystals represents one of the major obstacles in obtaining
the detailed 3D structure of a biological macromolecule. The complete automation of the …

Predicting and controlling crystallinity of molecular materials has applications in a crystal
engineering context, as well as process control and formulation in the pharmaceutical …

Background Current protocols yield crystals for< 30% of known proteins, indicating that
automatically identifying crystallizable proteins may improve high-throughput structural …

Motivation: X-ray crystallography-based protein structure determination, which accounts for
majority of solved structures, is characterized by relatively low success rates. One solution is …

Chromatography is widely used in biotherapeutics manufacturing, and the corresponding
underlying mechanisms are well understood. To enable process control and automation …

In the current report, three machine learning approaches were assessed for their ability to
predict the crystallization propensities of a set of small organic compounds (< 709 Da). The …

Pavement deflection data are often used to evaluate a pavement's structural condition non-
destructively. Pavement layers are characterized by their elastic moduli estimated from …

The accurate prediction of whether a protein will crystallize plays a crucial role in improving
the success rate of protein crystallization projects. A common critical problem in the …