Distribution of Bound Conformations in Conformational Ensembles for X‑ray Ligands Predicted by the ANI-2X Machine Learning Potential حسب Fengyang Han (14613218)

"…In this study, we systematically studied the energy distribution of bioactive conformations of small molecular ligands in their conformational ensembles using ANI-2X, a machine learning potential, in conjunction with one of our recently developed geometry optimization algorithms, known as a conjugate gradient with backtracking line search (CG-BS). …"

Probability flux balances can determine biochemical rates regardless of global network dynamics. حسب Timon Wittenstein (12908474)

"…Although probability distributions differed greatly between the four systems, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010183#pcbi.1010183.e006" target="_blank">Eq (4)</a> could identify the functional dependence of the production rate of X₃ based on the numerical convex optimization algorithm detailed in the Materials & Methods. …"

Methodology block diagram. حسب Gahao Chen (21688843)

"…Six machine learning algorithms - Random Forest (RF), AdaBoost, Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), and Tabular Prior-data Fitted Network version 2.0 (TabPFN-V2) - were implemented with five-fold cross-validation to optimize model hyperparameters. …"

Rendered image volumes in the MIPAV GUI. حسب Andrew Lauziere (14192836)

The Geography of Oxia Planum 03 CTX DEM Mosaic حسب Peter Fawdon (10016036)

"…The CTX mosaic data was rectified using the spline transformation. which optimizes for local accuracy but not global accuracy (Esri, 2020). …"

Figures and Tables حسب Divya C D (22799186)

"…Robots Comput. Vision XXXI: Algorithms and Techniques, Burlingame, CA, USA, Jan. 23–24, 2012.…"