Scientists at St. Jude Children's Research Hospital have reconciled two closely related but contentious mechanisms underlying ...

Researchers in Korea have developed an artificial intelligence (AI) technology that predicts molecular properties by learning ...

Focusing on molecular prognostic models in LR-MDS, Jamie Koprivnikar, MD, shares insights gleaned from the COMMANDS trial on how mutational burden impacts response. 70-year-old man diagnosed 6 months ...

We introduce the general transition-based reweighting analysis method (TRAM), a statistically optimal approach to integrate both unbiased and biased molecular dynamics simulations, such as umbrella ...

Latent variable models are widely used to perform unsupervised segmentation of time series in different context such as robotics, speech recognition, and economics. One of the most widely used latent ...

In this talk, I will introduce why approximating protein dynamics with a Markov model is a valid approach and then will explore the good, bad and, ugly when it comes to trying to automate the building ...

With recent advances in structural biology, including experimental techniques and deep learning-enabled high-precision structure predictions, molecular dynamics methods that scale up to large ...

Acceptance summary: This article presents state-of-the-art molecular dynamics simulations of the pH-gated pentameric ion channel GLIC, which has been the subject of many structural and functional ...

In molecular dynamics simulations, these data-driven collective variables capture the slowest modes of the dynamics and are useful for enhanced sampling and free energy estimation. In this work, we ...

Future smart grid operations must rely upon accurate state estimation (SE). Estimation at the distribution level is very challenging since the customary monitoring infrastructure inhibits access to ...