We have 4 of 8 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
The resources and modeling advances supporting AI virtual cells' value for mechanism-of-action analysis, efficacy, safety, resistance, and combination studies are reviewed, and evidence requirements for pharmacological use are defined.
Structure-sensitive properties (SSPs), including activity cliffs and chirality-dependent properties, challenge molecular machine learning because small structural perturbations can cause abrupt property changes and invalidate smooth structure–property assumptions. Here, we present CAMF (Chirality- and Activity-cliff-aw...
TPS-Flow is presented, a physics-guided flow-based generative framework for end point-conditioned conformational path sampling between predefined protein states (not equilibrium ensembles), thereby bridging atomistic simulation and deep generative modeling of protein transition paths.
CoBind is presented, a multitask deep learning framework that jointly predicts RNA–compound interactions and nucleotide-level binding-site probabilities within a unified architecture and provides complementary nucleotide-level binding-site localization, supporting a site-aware view of RNA–ligand recognition under distr...
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
