A computational method for finding transition states in chemical reactions, greatly reducing computational costs with high reliability, has been devised. Compared to the most widely used existing ...
A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...
Meshfree methods have emerged as a powerful alternative to traditional finite element approaches by eliminating the reliance on fixed meshes for domain discretisation. These techniques, which include ...
Computational Chemistry is the study of complex chemical problems using a combination of computer simulations, chemistry theory and information science. Also called cheminformatics, this field enables ...
Researchers propose a computational method to reveal the hidden timing structure of live performance. Vanessa C. Pope and ...
Discontinuous Galerkin (DG) methods have emerged as a formidable tool in computational fluid dynamics (CFD), offering a flexible and high-order accurate framework for solving complex flow problems. By ...
New AI memory method lets models think harder while avoiding costly high-bandwidth memory, which is the major driver for DRAM ...
The new method can determine crystal structures underlying experimental data thus far difficult to analyze. A joint research team led by Yuuki Kubo and Shiji Tsuneyuki of the University of Tokyo has ...
In order to understand metabolic processes, it is important to be able to detect critical individual elements and metabolites in living organisms. Researchers from Heinrich Heine University Düsseldorf ...
Scientists at La Jolla Institute for Immunology (LJI) have developed a new computational method for linking molecular marks on our DNA to gene activity. Their work may help researchers connect genes ...
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