H-bonded assembly of multiple components into well-defined icosahedral capsules has been elusive, and constructing stable sophisticated cluster-based supramolecular frameworks without coordinative bonding linkages remains challenging. Here, the authors report a cluster-based icosahedral H-bonded capsule Cu60 ...
Regarding the principle of constructing graph models based on risk correlation relationships, if important positions are not thoroughly mastered, it would increase the risk of not comprehending other associated items. Therefore, the item kp.46, as a necessary point, which occupied a crucial position ...
Contrastive learning usually aims to enable network learning to parse high-level representations of images, in which similar instances are more tightly coupled together in latent space because of akin features, while different instances are relatively far away. (For example, any photograph of a person...
However, these graphs cannot maintain the latent correlation and attribute of the wind turbines, leading to inferior performance. This research proposes an optimizing wind power prediction model through attention mechanism and spatiotemporal graph neural networks. Initially, the spectral clustering and a ...
using small datasets. Overall, the annotation and quantity limitations of data when using supervised learning to train models have become the main challenges for deep neural networks in medical image diagnosis applications, limiting research on constructing effective models in different clinical use cases...
DeepMSA: constructing deep multiple sequence alignment to improve contact prediction and fold-recognition for distant-homology proteins. Bioinformatics 36, 2105–2112 (2020). Article Google Scholar Wu, N. et al. Solution structure of Gaussia luciferase with five disulfide bonds and identification of ...
Transformer-based protein generation with regularized latent space optimization Article 26 September 2022 Low-N protein engineering with data-efficient deep learning Article 07 April 2021 Machine learning-guided co-optimization of fitness and diversity facilitates combinatorial library design in enzyme ...
In the context of language acquisition, this theory underscores the significance of peer collaboration in constructing knowledge and language skills. The Zone of Proximal Development (ZPD) concept suggests that learners can achieve more with the support of peers who are slightly more proficient, ...
Advancements in deep learning and computer vision provide promising solutions for medical image analysis, potentially improving healthcare and patient outcomes. However, the prevailing paradigm of training deep learning models requires large quantities o
The first direct choice for constructing SSL tasks is the inherent structure information contained in BioHNs. For a given node, self-supervision information is not only limited to itself or local neighbours, but also includes a bird’s-eye view of the node positions in a BioHN. We therefore...