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Automating retrosynthesis with artificial intelligence expedites organic chemistry research in digital laboratories. However, most existing deep-learning approaches are hard to explain, like a “black box” with few insights. Here, we propose RetroExplainer, formulizing the retrosynthesis task into a mole...
Aaditya Ramdas is an assistant professor in the Departments of Statistics and Machine Learning at Carnegie Mellon University. His research interests are selective and simultaneous inference, sequential uncertainty quantification, and assumption-free black-box predictive inference.View...
et al. Nonlinear Prediction of Landslide Stability Based on Machine Learning | [基于 Box⁃Jenkins 随机模型的滑坡稳定性预测模型]. Diqiu Kexue - Zhongguo Dizhi Daxue Xuebao/Earth Science - Journal of China University of Geosciences, 2023, 48(5): 1989-1999. DOI:10.3799/dqkx.2023.036 64. ...
The protein molecule was immersed in a 70.4 × 65.9 × 70.6 Å3 periodic box of TIP3P water molecules (7680 water molecules and 25,501 atoms in total). The long-range electrostatic interactions were treated using the particle-mesh Ewald method. The systems were energy minimized by the...
box, and rarely consider the environmental information in traffic scenes and the interaction between traffic objects, a pedestrian crossing intention prediction method based on multi-modal feature fusion is proposed. In this paper, a new global scene context information extraction module and a local ...
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databox com.azure.resourcemanager.databox.fluent com.azure.resourcemanager.databox.fluent.models com.azure.resourcemanager.databox.models com.azure.resourcemanager.databoxedge com.azure.resourcemanager.databoxedge.fluent com.azure.resourcemanager.databoxedge.models com.azure.resourcemana...
Convolution-neural-network-based MolMapNet models were constructed for out-of-the-box deep learning of pharmaceutical properties, which outperformed the graph-based and other established models on most of the 26 pharmaceutically relevant benchmark datasets and a novel dataset. The MolMapNet learned ...
In contrast to Δgainability, we found negative Δdisruptability scores for forkhead, homeodomain, nuclear receptor, rel, sox and T-box families across most of the 20 cancer-types analyzed (Fig. 4b). These results suggest a negative selection towards disrupting TFBSs for these families. Contrary...