In short, this hierarchical graph approach aims at modeling the natural PPI hierarchy with more effective and efficient structure perceptions. Here we describe a generic DL platform tailored for predicting PPIs, Hierarchical Graph Neural Networks for Protein–Protein Interactions (HIGH-PPI). HIGH-PPI m...
We used the short-root (SHR) promoter, which is exclusively active in the stele, the central tissue of the root, and drives the expression of SHR14. The latter is a nucleus-localized transcription factor that moves from the stele, where it is synthesized, to the endodermis, a tissue ...
First, starting from the existing values of their RNA counterparts (uracil beads in case of thymine, and ribose GS2 bead for deoxyribose GS2), σ parameters were optimized to provide possibly low root mean square deviation (RMSD) of protein Cα atoms after rigid body energy minimization of ...
Opposed to the role of inflammatory or adrenergic receptors in hyperalgesia, stimulation of opioid receptors in the cell bodies in the dorsal root ganglion (DRG) and on primary afferent neurons triggers analgesia. Opioids act on different types of GPCRs (MOR, DOR, and KOR) coupled to Gi/o ...
During model training, a third stage computes deviations between predicted and experimental structures using the distance-based root mean square deviation (dRMSD) metric. The dRMSD first computes pairwise distances between all atoms in the predicted structure and all atoms in the experimental one (...
To run a Jupyter notebook instance inside the container, run : jupyter notebook --ip=0.0.0.0 --port=8888 --allow-root The steps above will install all necessary packages and create the environment to run binding predictions using AI-Bind. ...
If SD was not reported in studies, it was calculated by multiplying the reported SE of means by the square root of the sample size. Given the heterogeneity among the studies and application of meta-regression to identify factors contributing to this heterogeneity, other sets of data were also ...
but short distance does not necessarily mean similar features. This leads to the graph not having strict homophily. To capture this important feature, it is natural to utilize heterophily-based models. However, to the best of our knowledge, no heterophily-based GNNs have been used for modelin...
Milk proteins and milk protein-derived peptides have been widely studied for their health enhancing properties. This chapter presents the updated scientific knowledge on the bioactive properties of milk protein-derived peptides. The different bioactive p
(uracil beads in case of thymine, and ribose GS2 bead for deoxyribose GS2),σparameters were optimized to provide possibly low root mean square deviation (RMSD) of protein Cαatoms after rigid body energy minimization of native complexes. The optimization was performed using Monte Carlo-like ...