A paper published in Biology Methods and Protocols, indicates that a new computational method may help researchers identify ...

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic ...

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 ...

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 ...

Organized by Scientific Explore Publications and coordinated from Madurai, Tamil Nadu, ICCMMAS 2025 featured technical ...

Researchers at The Hong Kong University of Science and Technology (HKUST) School of Engineering have developed a novel reinforcement learning–based generative model to predict neural signals, creating ...

A team of physicists has developed a groundbreaking method for detecting congestive heart failure with greater ease and precision than previously thought possible. This multidisciplinary study, ...

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 ...

Future events such as the weather or satellite trajectories are computed in tiny time steps, so the computation must be both efficient and as accurate as possible at each step lest errors pile up. A ...

Schematic image of X-ray data-enhanced computational method. Image Credit: University of Tokyo The method predicts structures directly from powder X-ray diffraction patterns, which are created when ...