A team of researchers has built a new protein sequencing workflow that pairs mirror proteases with deep learning software to read peptide sequences with far greater accuracy than previous methods.

The proton-conducting layer currently found in solid oxide fuel cells is typically made from a perovskite structure (left). Using machine learning, a research team, led by Kyushu University, has ...

Figure 1. This figure depicts the four categories of protein druggability target screening tools discussed in this section, which include structure-based methods, sequence-based methods, machine ...

Machine learning models trained on molecular quadrupole moments predict electrostatic potentials rapidly, enabling faster ...

20+ Machine Learning Methods in Groundbreaking Periodic Table From MIT, Google, Microsoft Your email has been sent A new “periodic table for machine learning” is reshaping how researchers explore AI, ...

Researchers have developed a framework that uses machine learning to accelerate the search for new proton-conducting materials, that could potentially improve the efficiency of hydrogen fuel cells.